Generative AI (GenAI) can transform product development, driving unprecedented efficiency, accuracy, and insight. As speed, team productivity, and delivering valuable tools become critical priorities, GenAI has become a necessity for organizations striving to stay ahead. It’s essential for organizations to aspire to lead in innovation and keep up with competitors. By harnessing GenAI in the product development lifecycle, companies have opportunities to transform how they plan and execute product development.

To illustrate GenAI’s impact on product development, we’ve identified 21 transformative ways it can reshape the product development lifecycle, helping you stay ahead, work smarter, and deliver results that drive business value.

Planning and Ideation

Innovative products with effective solutions start with strategic planning, ensuring that each decision is aligned with business value, addressing customer needs and driven by market trends. Here’s how GenAI can be used to dramatically impact your business outcomes during the planning and ideation phase:

1. Product Ideation – Use GenAI to generate product capabilities, augmenting the team’s expertise by providing valuable research and insights that may reveal additional competitive advantages the team hadn’t considered.
2. Market Analysis – Accelerate and reduce the time to perform research with GenAI, classifying and evaluating trends across industries.
3. Competitive Analysis – Conduct competitive and comparative analysis to uncover strategic opportunities, identify gaps, and inform product positioning for long-term success.
4. Persona Creation – Generate synthetic personas to be able to conduct real-time interviews and ongoing testing to be able to inform the user journey in addition to human-based personas and potentially gather additional insights.

Design

Effective design allows users to conduct their tasks as efficiently as possible while enjoying the experience. Use GenAI to accelerate design and provide opportunities for real-time feedback.

5. Requirements Generation – Draft and validate requirements against industry and organizational standards, industry knowledge, and accelerating delivery of business-ready requirements to stakeholders and reducing stakeholder effort.
6. User Story Creation – Draft stories from requirements and validate the stories across the entire product portfolio for standards and consistency, accelerating development-ready stories.
7. Prototyping and UX Design – Rapidly create design concepts and functional prototypes, gathering feedback and expediting early-stage ideation and review cycles.
8. Roadmap Prioritization – Prioritize features based on delivery of value, balancing cost complexity and time, and ensuring we prioritize the most important capabilities.

Engineering

Engineering relies on high-quality backlog items and detailed design and GenAI and accelerate development allowing an organization to ship products faster:

9. Code Generation & Migration – Automate repetitive tasks, letting developers focus on more complex challenges.
10. Accelerate Understanding of Existing Code – Use GenAI to analyze and explain current functionality, accelerating development, and preventing duplication.
11. Automated Refactoring – Use GenAI to look for opportunities for refactoring and reduce the effort on the engineer, reducing technical debt and increasing maintainability.
12. Infrastructure Generation – Scaffold typical infrastructure environments and reduce time-sink tasks for engineers, reducing the burden of environments for specific uses.
13. Performance & Optimization – Proactively assess and optimize code to preempt bottlenecks and improve overall product performance.

Quality

Quality and testing are a significant investment for organizations and have a high-labor cost even with automation. GenAI accelerates and provides efficiencies beyond traditional automation approaches:

14. Automatic Test Generation – Acceptance criteria enrichment, automatically generate test cases, covering scenarios critical for updates.
15. Self-Healing Tests – Implement tests that adapt to code changes, maintaining testing as products evolve and change.
16. Persona & Scenario Test Data – Generate synthetic test data for real-world scenarios, persona-based simulations, and dramatically increase test coverage.
17. Performance Testing – Automatically define test criteria and metrics to assess overall product performance, identify recurring defects, and highlight bottlenecks in the QA test suite..

Operations

Efficient operations ensure predictability, governance, and cost-effectiveness, enabling organizations to deliver reliable, high-performing tools and experiences for employees and customers. Here’s how GenAI can enhance your operations:

18. Process Automation – Automate time-consuming tasks, freeing your team for more valuable activities.
19. Security & Incident Response – Continuously protect infrastructure and systems with AI-powered threat detection and decreased incident resolution time.
20. Event Correlation & Analysis – Correlate events across systems to identify patterns, predict issues, and self-heal to increase up-time.
21. Anomaly Detection – Identify patterns and detect anomalies to proactively address system issues.

By identifying opportunities and adopting GenAI across these 21 key areas, product development cycles can become more agile, efficient, and innovative. Whether focused on planning, design, engineering, quality, or operations, GenAI empowers teams to create, refine, and launch digital products faster and deliver value to the business faster.

Moving Forward with GenAI

Adopting GenAI is a critical step in delivering products that meets their audience needs more efficiently with greater value. With 75% of CEOs acknowledging the advantage of advanced AI capabilities, the use case for proactive AI adoption has never been stronger.

Ready to start adopting GenAI in your product development? Contact us to learn more about our position on AI-Driven Product Development and how GenAI can revolutionize your product strategy and set your organization on a path to innovation, growth, and business value.

Don’t know where to start? Talk to us about AI AMP, our accelerated model process to ideate AI solutions that will have a measurable impact on your business.

Our Adobe experts are heading to Vegas this month to attend Adobe Summit, connect with industry leaders, and learn about Adobe’s latest innovations. The conference will provide plenty of opportunities to learn how to grow your business and deliver exceptional digital experiences.

In the video below, Perficient principals Robert Sumner and Ross Monaghan have identified the top three topics they are excited to hear about: GenStudio, the rise in B2B features, and personalization.

Check out the video and learn more about why they’re excited and make sure to check out all the ways you can engage with us if you’re attending Summit as well.

Watch: Why Our Experts Are Excited About GenStudio, B2B, and Personalization

Meet Us at Adobe Summit

Going to Adobe Summit? Find out how to connect with us!

Learn more. 

Perficient is a recognized leader in artificial intelligence solutions, especially as it relates to generative AI, empowering enterprises to accelerate AI adoption, and transform operations. With deep expertise across Google, Adobe, Salesforce, Microsoft, and AWS technologies, we design and deploy scalable, high-impact solutions that drive efficiency, innovation, and measurable business outcomes across industries.

Our experts regularly engage in thought leadership, such as blogs discussing the benefits of AI and strategic positions, in addition to their transformational work for clients. Recently, Perficient’s work with a leading automotive manufacturer’s GenAI virtual assistant was included in Forrester’s Report titled “Design GenAI-Powered Experiences Responsibly,” which discusses how to ensure generative AI solutions are functional, efficient, and, most importantly, safe and responsible.

Why Design Responsibly? Potential for Positive and Negative Outcomes

AI’s potential to save time and boost efficiency has led many companies to quickly implement its use in the workplace with administrative functions like HR, legal, and procurement being early adopters. While these benefits are attractive, many worry about the downsides of these implementations. The flipside could potentially make experiences worse and harm both users and organizations alike.

If GenAI is deployed correctly, it can provide easier daily tasks and boost employee productivity, especially among individuals with disabilities. Chatbots can greatly reduce the challenges faced by people by being able to gather information from multiple sources quickly and produce a coherent summary.

While there are many positives with AI deployment, it could also lead to grave consequences. According to Forrester, “The AI Incident Database, which tracks AI harms, listed over 3,600 reports of incidents spanning categories from misinformation to autonomous vehicle fatalities as of September 2024.”  Chatbots and other AI have been known to provide advice that is detrimental and biased, reducing their effectiveness and disadvantaging those they were designed to support, thus furthering public distrust of AI.

Responsible Design Starts Within the Institution

How do you design responsibly to avoid the pitfalls? Through proper internal governance and culture creation, organizations can build a structure that supports responsible design decisions. With these parameters in place, individuals working on design will feel empowered to uphold these principles in their GenAI designs.

“When designing with AI, teams should ask essential questions: Did we leave anyone out of this experience? Did we conduct user research with the target audience and validate our UX designs with them? Do we provide the proper training to design responsibly? Answering these questions will point teams in the right direction for every project.” — Lisa McMichael, Senior Manager Digital Accessibility, Perficient

At the Forrester CX Summit North America in 2024, the author of this report, Principal Analyst Gina Bhawalkar, presented Perficient’s work with this automaker during her session. The presentation outlined that when approaching the project with a leading automotive manufacturer, our team defined several tiers for generating responses versus delivering curated responses. The goal was to ensure the AI virtual assistant provided the best information to customers based on the nature of their inquiries.

For example:

1. For safety-related questions, we deliver curated responses to ensure precise verbiage.
2. For product questions, we allow the AI to generate responses using information from the website.
3. We use pre-trained knowledge to deliver information on general queries like “What is an SUV?”

In doing so, the team was able to improve the accuracy of the answers offered to users and lessen the risk that higher-sensitivity topics like safety would be handled irresponsibly. Further, the team set principals such as offering suggestions for the user to get started when landing on the site. A full case study outlining this project can be found here.

Ready to develop artificial intelligence solutions responsibly? Explore Perficient’s GenAI expertise.

As I gear up for my presentation at the Adobe Summit this March, I’ve been reflecting on the transformative potential of a well-executed content supply chain—and the hurdles large organizations face in making it a reality. And since it is Summit, I will obviously be referencing tools like Adobe GenStudio, Adobe Workfront, AEM Sites, and AEM Assets, which all aim to streamline content creation, management, and activation. Yet, one pain point consistently rises to the top when implementing this process at scale: siloed teams and disconnected workflows.

The #1 Barrier to an Efficient Content Supply Chain

In large organizations, it is practically impossible to audit the content generation processes because content production often resembles a patchwork quilt rather than a seamless assembly line, with each patch representing a different department or agency. The patches themselves represent the individual departmental processes, which makes stitching them together difficult.

For example, the Marketing team might be crafting campaigns within the agency, while design teams work in isolation on visuals that get handed off to the dev team for assembly within their isolated channel teams.  This fragmentation isn’t just a minor inconvenience—it’s the number one barrier to achieving an efficient content supply chain.

This pain point isn’t insurmountable, however. The Adobe Experience Cloud is designed specifically to bridge these process clusters to help orchestrate tasks across teams, ensuring everyone—from copywriters to legal reviewers—is aligned on timelines and deliverables. Now coined GenStudio from Adobe, Adobe has invested significant dollars into creating one holistic solution to streamline content development. The trick is getting everyone on the same page.

Simply Buying Tech Won’t Solve Your Content Supply Challenges

Ok, so, yes, it’s the age-old adage of people and processes and not just technology. You probably didn’t need to read this to figure that out, but if it is so obvious, why do so many large organizations struggle to improve? My observation is this: if you don’t have the proper change management and cross-functional training in place and if you can’t foster and establish a cultural shift toward collaboration, then all the technology in the world won’t help, making leadership buy-in is critical.

At Adobe Summit, my plan is to review the technology elements but to also dive deeper into how organizations can tackle this pain point head-on, with real-world examples and practical strategies. We have to start by connecting the dots—and the people—behind the content, unlocking the full potential of the organization to scale up content production.

Stay tuned for more insights as I prepare for March, and let me know your thoughts on streamlining content workflows in the comments!

Attending Adobe Summit 2025?

Join us for lunch during Adobe Summit to explore why having a clear, strategic vision is essential before deploying new technologies. We’ll discuss how GenStudio and other tools can fit into your existing content workflow to maximize efficiency and creativity.

We hope to see you there!

Beyond GenStudio: Crafting a Modern Content Supply Chain Vision
Wednesday, March 19 | 11:30 A.M. – 1:30 P.M.
Register

The 2025 National Conference on Artificial Intelligence is an unparalleled opportunity to dive deep into the transformative potential of AI across various sectors. With topics ranging from responsible AI to workforce development, this conference explores the vast possibilities of AI. 

I am thrilled to be leading a panel discussion on AI in healthcare at this year’s conference, taking place from April 9-11. As a third-year speaker for this event, I am excited to share why this event is pivotal for the healthcare industry and why you should be a part of it. 

Key Topics in AI 

The following topics are expected to be top-of-mind during the conference; these include: 

1. Generative AI (GenAI) in Healthcare: Explore the latest advancements and applications of GenAI in the healthcare sector. 
2. AI Adoption and Implementation Strategies: Learn about best practices and success stories from industry experts on implementing AI solutions effectively. 
3. Data-Driven Decision Making: With the increasing reliance on data-driven decision making in various industries, understanding how AI can support this process is crucial. 
4. Cybersecurity for AI Systems: As AI becomes more prevalent, cybersecurity concerns are growing. It’s important to learn about measures to protect against potential threats and vulnerabilities. 
5. Ethics and Bias in AI: With the increasing use of AI, there is a growing need to address ethics and bias in AI decision-making processes. 
6. AI for Healthcare Outcomes Improvement: Discover how AI can improve healthcare outcomes, such as patient care, disease diagnosis, and treatment planning. 
7. Emerging Trends in Natural Language Processing (NLP): NLP is a key aspect of GenAI, and staying up to date on the latest developments and applications is essential. 

Perficient’s approach to these topics is grounded in our PACE framework, which provides a holistic approach to responsibly operationalizing AI and GenAI across an organization. The PACE framework empowers organizations to unlock the benefits of AI while proactively addressing risks. 

I find all the sessions at the National Conference on Artificial Intelligence valuable, but I especially enjoy the panel discussions and networking opportunities. I have an abiding commitment to continuous learning and educating new people in AI and healthcare. Clinicians need support and training to take care of patients today and in the future. 

The Importance of Workforce Development in AI 

The future of AI relies heavily on a skilled workforce capable of developing, implementing, and maintaining these cutting-edge technologies. A strong focus on workforce development ensures that we can: 

• Address Skill Gaps: Identify and address skill gaps in NLP and AI development to ensure our clients have access to the expertise they need. 
• Drive Innovation: Foster a culture of innovation by investing in ongoing training and education for our employees, enabling them to stay up to date with the latest advancements in NLP and GenAI. 
• Attract Top Talent: Attract top talent from academia and industry, ensuring that we have access to the best minds in NLP and AI development. 
• Continue to Lead the Nation: Lead the nation in the development and adoption of AI solutions that benefit all of society.  

Did You Know: We’re also advancing STEM education through our award-winning partnership with the Mark Cuban Foundation. Learn more about the free Artificial Intelligence (AI) Bootcamps that we host for high school students across the United States.

Get Ready for the Future of AI 

Let’s connect at the 2025 National Conference on Artificial Intelligence in Houston to explore the future of AI in healthcare. I’m excited to share insights and innovations with you as I lead a panel discussion on AI in healthcare. Connect with me today to schedule time to meet at the conference! 

We are trusted by leading technology partners, mentioned by analysts, and Modern Healthcare consistently ranks us as one of the largest healthcare consulting firms. Discover why we have been trusted by the 10 largest health systems and the 10 largest health insurers in the U.S. Explore our healthcare expertise and contact us to learn more.

A friend recently shared a research paper from Oxford Academic about Large Language Models (LLMs) and their human-like biases. I found it fascinating.

The article explains how some groups use LLMs to simulate human participants. Since these models are trained on human-generated data, they can emulate human responses across diverse psychological and behavioral experiments.

It further notes that LLMs favor socially desirable responses that align with the Big Five personality traits – including agreeableness. Notably, during their experiments, LLMs would modify the responses if the researcher appeared to be evaluating it.

Confidently Wrong AI (Posturing)

I had planned to write about the phrase “confidently wrong,” which we hear often when talking about Artificial Intelligence (AI) models. Combined with the concept of AI hallucinations, this can mislead people who are expecting reliable answers from these tools.

More and more users are favoring AI over traditional online search. No doubt you’ve noticed that Google now shows an AI response above the SERP. This experience is often faster and feels more natural than manual trial-and-error clicks through links.

However, it becomes risky when the LLM is wrong. Once the AI selects an answer, it may be reluctant to admit it was wrong. Even if you challenge a correct statement, the LLM might apologize and change its answer to be agreeable. Users need to be cautious and validate the information received.

Confidently Incorrect Humans (Learning)

I have an 11-year-old son who is hell-bent on being contradictory. If I say the sky is blue, he’ll point out that it can be gray, yellow, orange, red, purple, or black. He’s not wrong, but he is frustratingly contrarian. When I tell him he’s being contradictory, he says, “No I’m not!” Even when he is flat wrong, he won’t let it go!

You’ve probably also heard the phrase “fake it ‘till you make it.” It’s meant to help those who are learning and to ease imposter syndrome. I used to hate the phrase because I prefer transparency. I’d rather hear “I don’t know” than to incorrectly think you have it under control. However, I now appreciate that it helps escape a negative mindset.

AI Confidently Mimicking Humans (Refining)

The Oxford Academic article points out that AI learns behaviors from us! It’s mostly trained on data created by humans, so it picks up our natural tendencies. If our writing is polite and avoids confrontation, the AI will be trained to follow those patterns.

Additionally, humans help validate the training – even crowdsourced to the general public. When you give a thumbs up to a response from an LLM, you’re teaching it what you prefer to see in the output. Over time it will lean toward agreeableness. While it’s not conscious, AI is learning to mimic humans.

The Con Man (Tricking)

The term “con man” or “con artist” comes from the word “confidence.” It refers to the act of manipulating or persuading people into believing something false.

Con artists have existed as long as humans have been able to communicate. There are fun ones, like magicians who amaze us with the spectacular. Then there are the bad kind that scam people out of their life savings. Even reputable sources like the BBC, CNN, Forbes, The Atlantic, and others can sometimes spread misleading information, confusing us even further.

AI is trained on a mix of data, including quality sources like scientific research papers but also the text of trolls attacking everything, and your mother, on Reddit. It learns from both the best and the worst of humanity.

The Confident Leader (Inspiring)

Confidence has two sides. We’re often inspired by confident leaders. When leaders seem uncertain, many people get nervous and may leave the group. It’s clear that we prefer a strong front over complete transparency.

Don’t get me wrong… We know that transparency is important. A quick Google search shows droves of experts saying that transparency is the best policy. We also understand the consequences of an over-confident leader.

But at the end of the day, we’re just regular folks looking for stability and security. Time and again, we’re attracted to leaders who exude confidence and instill inspiration.

Conclusion

We often laugh at poorly executed AI – it makes us feel superior. The same goes for poorly articulated statements from people – it makes us feel superior. We’ve all seen how we collectively attack and criticize each other online.

AI learns from us. It relies on us for continual improvement. It adopts our positive traits but can also mimic our negative behaviors.

As we continue to use AI, it will become a bigger part of our lives. Often, we’ll seek out the interaction, while other times, hidden AI will quietly work in the background. Just like with other people, we need to validate our interactions with AI. Trust, but verify.

……

If you are looking for a strong partner that loves AI but will verify results, reach out to your Perficient account manager or use our contact form to begin a conversation.

As we progress through 2025, the banking industry is set for substantial transformation driven by several key trends. Digital transformation will remain a powerful force, with advancements in AI and machine learning enabling unparalleled operational efficiencies and hyper-personalized customer experiences. Banks will look to transform the way they do business by moving beyond their walls with the maturing of open banking and embedded finance.

To stay competitive, banks must adapt and embrace emerging industry trends. This will require being more inquisitive and innovative compared to previous years, as the adoption of AI and cloud technologies continues to expand.

Banking Trend #1: Hyper-Personalization for Customer Satisfaction

Customers increasingly demand personalized banking experiences tailored to their unique needs and preferences. Hyper-personalization transforms the traditional banking model into a customer-centric approach, significantly boosting satisfaction and retention rates. Banks can use advanced data analytics and AI to deliver highly personalized financial services, such as customized savings plans and tailored investment advice. By leveraging data, banks can anticipate customer needs and proactively offer solutions, like recommending mortgage products or providing financial wellness tools based on individual spending patterns. Delivering these tailored experiences will be a crucial differentiator for banks aiming to attract and retain customers.

Recommended Approach: Banks should leverage advanced data analytics, artificial intelligence (AI), and machine learning (ML) to create highly individualized experiences. By understanding customer preferences, behaviors, and financial needs in real-time, banks can offer tailored products, services, and communication, leading to a more seamless and intuitive customer experience. This approach improves engagement and loyalty, increases revenue opportunities, and provides competitive differentiation.

See Also: Transforming Industries, Powering Innovation

Banking Trend #2: Adapting to Regulatory Shifts

As the banking landscape evolves, staying compliant with regulatory requirements becomes increasingly challenging, especially with the rise of open banking, AI, and data privacy concerns. In 2025, banks will face a more complex regulatory environment, with new rules focused on data privacy, cybersecurity, and sustainability. The rise of digital banking, cryptocurrency, blockchain, and AI adoption across banking operations will prompt regulatory bodies to implement clearer frameworks and guidelines to ensure stability and consumer protection.

Recommended Approach: Navigating constant changes in risk and regulatory environments is crucial for banks in 2025. By ensuring compliance with regulations, banks mitigate risks and maintain trust with customers and regulatory authorities. To stay ahead, banks should adopt compliance technologies that automate regulatory reporting and help them stay agile in a rapidly changing landscape. Investing in advanced technologies like AI and machine learning can help identify potential risks and streamline compliance efforts. By adopting these strategies, banks can better manage the dynamic risk and regulatory environment, ensuring compliance while maintaining competitiveness and customer trust.

Related: Strategies + Solutions to Ensure Regulatory and Compliance Excellence

Banking Trend #3: Embedded Finance Enables Industry Crossover

Embedded finance integrates financial services into non-financial platforms, allowing users to access banking services within applications they already use. By embedding payment, lending, and insurance services into apps and websites, non-financial companies are able to offer financial products directly to their customers. For example, ride-sharing apps like Uber and Lyft offer in-app payment options, and e-commerce platforms provide financing options at checkout. By integrating financial services into non-financial platforms, banks can tap into new markets and customer bases, generating additional revenue.

Recommended Approach: Banks looking to start or deepen their embedded finance solutions should take several key steps. These steps include identifying strategic partnerships and collaborating with fintech companies and non-financial platforms that align with their goals. These partnerships provide the necessary technology and customer reach to implement embedded finance solutions effectively. Next, invest in technology by upgrading IT infrastructure to support embedded finance, including adopting cloud-based solutions and modern technologies that offer the agility and scalability needed for seamless integration. Create robust APIs that allow third-party platforms to integrate your financial services. Ensure these APIs are secure, reliable, and easy to use. Leverage advanced data analytics to understand customer behavior and preferences, helping you offer personalized financial services that meet the specific needs of your customers.

You May Enjoy: 6 Digital Payment Trends Set to Transform 2025

Banking Trend #4: Leveraging AI for Insights and Automation

AI and automation have evolved from buzzwords to essential components of banking operations. In 2025, AI will play a pivotal role in customer service, fraud detection, risk management, and personalized financial advice. AI-powered chatbots will handle routine customer inquiries, freeing human agents to tackle more complex issues. Additionally, AI-driven algorithms will enhance banks’ ability to detect emerging fraud patterns and mitigate risks more effectively. Automation will streamline internal processes, leading to cost reductions and improved operational efficiency.

Recommended Approach: To fully utilize AI, banks need to prioritize improving their data strategy, recognizing that high-quality, reliable, and trustworthy data is essential for AI to deliver significant outcomes. They need to align AI initiatives with the bank’s overall business goals. Then identify areas where AI can add the most value, such as customer service, fraud detection, and risk management and focus on value-driven AI use cases. They also need to invest in modern technology and infrastructure for agility and scalability.

Read More: Transform Your Business With Cutting-Edge AI and Automation Solutions

Banking Trend #5: Responsive Resilience

Responsive Resilience continues to be a key banking trend in 2025, emphasizing the ability of financial institutions to adapt swiftly and effectively to changing conditions. Banks must be prepared to respond to economic fluctuations, market changes, and unexpected events. This requires robust risk management frameworks and the ability to pivot strategies quickly. A compounding factor, the shift to digital has caused increased exposure to financial fraud and cyber threats.

Recommended Approach: Invest in advanced technologies such as AI, machine learning, and cloud computing to enhance operational efficiency and adaptability. These technologies can automate processes, improve decision-making, and provide real-time insights. Utilize data analytics to gain deeper insights into customer behavior, market trends, and potential risks. This data-driven approach allows banks to make informed decisions and respond swiftly to changes in the banking landscape.

Explore More: Reimagine Business for the Digital Age

Banking Trend #6: Embracing Open Banking and Connected Ecosystems

Although many institutions have deprioritized open banking in recent years, establishing an open banking strategy now offers significant benefits. Open banking continues to revolutionize the financial industry by enabling secure data sharing between banks and third-party providers through APIs. It unlocks a wealth of third-party financial data, enabling banks to better-tailor products and services, enhance customer loyalty, improve operational efficiencies, and open new revenue streams. This trend will change how banks engage with third-party financial service providers, fostering the development of innovative financial products and services. Open banking will drive greater competition, promote collaboration, and empower consumers with more choices and personalized banking experiences. Examples include budgeting apps that aggregate data from multiple bank accounts, personalized financial advice based on spending patterns and streamlined loan application processes by accessing a customer’s financial data to provide a more accurate and personalized credit score.

Recommended Approach: Banks must establish a clear vision for open banking that aligns with their overall business goals. They should determine specific objectives, such as driving innovation, improving customer experience, or expanding market reach. Additionally, banks need to update their IT infrastructure to support open banking. This includes developing secure and reliable APIs for data sharing and ensuring systems are resilient and scalable.

See Also: 1033 Open Banking Mandate Blueprint for Success

Unlocking New Opportunities in 2025

Our end-to-end digital solutions drive business outcomes, enhance experiences, and ensure robust risk and compliance management to improve operational efficiency and business resilience.

• Business Transformation: Align the business with an actionable roadmap to optimize operations, improve service, and enhance profitability.
• Modernization: Advance technologies to enhance digital capabilities and customer engagement.
• Data + Analytics: Proactively leverage integrated data and AI to refine banking product portfolios and mitigate risks.
• Risk + Compliance: Strengthen risk management frameworks, ensure adherence to banking regulations, and enhance operational stability.
• Consumer Experience: Improve customer satisfaction with hyper-personalized banking services and intuitive digital experiences.

Discover why we have been trusted by 18 of the 20 largest commercial banks. Explore our financial services expertise and contact us to learn more.

Driven by factors ranging from generational wealth transfer to technological advancements, Perficient’s Principal in Wealth and Asset Management, Gerardo Montemayor, provides valuable insights into the wealth management trends set to transform the industry in 2025.

Wealth Management Trend #1: Hyper-Personalized Experiences With AI

Driven by advancements in AI, big data, and machine learning, hyper-personalization is reshaping wealth management firms’ ability to tailor financial services based on individual preferences, behaviors, and investment goals. This transformation has been accelerated by a confluence of shifting client demographics and expectations along with mounting competitive pressure from emerging tech-driven players, financial product innovation, and industry consolidation. To remain competitive, wealth managers are driven to strengthen client relationships, redefine client experience, foster loyalty, deepen engagement, and drive long-term growth.

Recommended Approach: By leveraging user research and behavioral analytics, journey sciences help define and optimize the user journey, supporting more-meaningful hyper-personalization that addresses customer needs and preferences at each touchpoint. AI, machine learning, and big data analytics for predictive insights and personalized financial strategies require well-governed, securely democratized data. Cloud computing and modern data integrations unlock the benefits of scalable data management and real-time collaboration while advanced visualization tools and API integrations with third-party data equip teams to isolate priority scenarios and accelerate deeply tailored outreach.

Learn More: Optimize Every Touchpoint

Wealth Management Trend #2: Client Advisor Empowerment

Empowered client advisors drive AUM growth. Wealth managers, meanwhile, aim to boost advisor collaboration and, together, grow their book of business. To be effective, both groups need the tools and insights to drive faster progress, efficiently delivering high-quality, proactively personalized service in less time and with fewer manual tasks. With those efficiencies in place, these important business contributors can focus on strategic, high-value activities—ultimately driving client acquisition, retention, and long-term growth.

Recommended Approach: Empower client advisors with cutting-edge technologies that enhance efficiency, provide deeper insights, and strengthen client engagement, transforming raw information into actionable insights that support personalized investment strategies and tailored financial advice. Strategically implemented AI, augmented analytics and visualizations can accelerate smarter decision-making, while intelligent automation equips teams to streamline processes, enhance efficiency, and drive significant cost savings. Ease client management and foster seamless collaboration with compliant CRM and messaging tools. Mobile and cloud-based solutions enable anytime, anywhere, access to critical data and tools, ensuring greater flexibility.

See Also: Speeding Insights and Powering Investment Experience

Wealth Management Trend #3: Navigating ESG in a Shifting Political Landscape

The political environment significantly influences the integration of Environmental, Social, and Governance (ESG) considerations in wealth management. With the current administration rethinking of ESG, regulatory frameworks are rapidly evolving, creating both challenges and opportunities for investors and their advisors. Despite federal pushback, state-level initiatives and international regulations, particularly from the EU, continue to drive the importance of ESG. Investors are increasingly focused on aligning their portfolios with personal values, financial goals, and global sustainability trends, even as they navigate a complex and often contradictory regulatory environment. This dynamic underscores the need for adaptability and vigilance in ESG investing.

Recommended Approach: Build regulatory agility without losing site of investors’ expectations and consider how digital efficiencies and advisor enablement can differentiate your brand experiences. Advanced analytics and AI can provide personalized scoring, risk assessment, and greenwashing detection, ensuring transparency and data-driven decision-making. Big data integration is crucial for obtaining a unified view of diverse data sources, supporting robust ESG insights – particularly as ESG reporting becomes more fragmented when no longer mandated. Additionally, proactive regulatory insights can equip your organization to mitigate risks and capitalize on new opportunities. By staying agile and informed, investors can continue to drive long-term growth and meaningful impact through sustainable investment strategies.

Success In Action: Elevating ESG in Wealth Management Portfolios

Wealth Management Trend #4: Omnichannel Access

Digital platforms are reshaping how investors monitor portfolio progress, driven by expectations for convenience, accessibility, and personalized services. Omnichannel tools enhance client experience by offering seamless access to investment portfolios, performance insights, and account management tools. These platforms not only serve existing clients but also expand wealth management services to a broader audience. Additionally, they enable a wider range of investment products, support a do-it-yourself (DIY) model, and facilitate more strategic client collaboration, allowing for deeper engagement and more effective financial planning.

Recommended Approach: Mobile and cloud-based solutions form the backbone of digital platforms, providing seamless, anytime-anywhere access to critical data and tools for greater flexibility. Automation platforms support the DIY model, streamlining administrative tasks and enhancing efficiency. Additionally, custom development allows wealth managers to differentiate their services, offering tailored solutions and personalized collaboration channels to strengthen client relationships.

Explore More: Future-Proof Your Tech Investment

Wealth Management Trend #5: Optimizing Operational Efficiencies

In the current macro-environment, wealth and asset management firms face rising costs, global volatility, increasing competition, and compliance challenges. Despite expanding industry assets and revenues, operating margins are under pressure, making profitability a top priority. Firms are also navigating a landscape of mergers and acquisitions, strategic outsourcing, and vendor consolidation to hone core strengths and boost a competitive edge. These business pressures drive the need for digital investments to enhance efficiency and maintain profitability.

Recommended Approach: Leverage a power combination of process mining and automation to streamline operational workflows and improve experiences. Process mining helps identify and prioritize inefficiencies, errors, and delays in complex business processes that are prime for optimization. Automation platforms, in turn, reduce costs by intelligently handling time-consuming tasks in back-office operations, portfolio management, reporting, and compliance, allowing advisors and client support teams to focus on what matters most: nurturing meaningful relationships and delivering value. By enhancing data quality and supporting advisors’ strategic planning efforts, these technologies drive scalability and sustainable growth, enabling firms to remain competitive. These advantages can be further amplified with a digital partner that offers robust, agile global delivery capabilities and platform relationships, maximizing cost savings without compromising quality and ensuring rapid deployments that drive business outcomes.

You May Enjoy: Transform Your Business With Cutting-Edge AI and Automation Solutions

Embrace the Future and Transform Your Wealth Strategy

We empower wealth and asset managers with proactive insights, hyper-personalized experiences, and proactive risk management to drive sustainable growth.

• Business Transformation: Develop and optimize strategies and processes for efficient wealth management operations.
• Modernization: Upgrade technology and processes to ensure seamless integration and enhanced, streamlined client advisor experiences.
• Data + Analytics: Harness data-driven insights for personalized investment strategies, client collaboration, and operational efficiency.
• Risk + Compliance: Implement robust strategies to safeguard investor relationships and ensure regulatory adherence.
• Consumer Experience: Enhance engagement and satisfaction with tailored advisory services and digital tools.

Discover why we have been trusted by 16 of the 20 largest wealth management firms. Explore our financial services expertise and contact us to learn more.

Leveraging data that is ‘trapped’ within unstructured data files like PDFs is a powerful capability within Agentforce.  With an Agentforce Data Library this ability to surface PDF content through an Agent is now available in a ‘No Code’ fashion to all Salesforce Admins.

So what is our Agentforce unstructured data use case?

Let’s say we have a variety of PDFs about the warranty coverage for vehicles.  We have a customer Experience Cloud site where the customer will log in and see their current warranty information. We also want these customers to be able to ask questions about the warranty program.   At this point all of that warranty information is ‘trapped’ inside of these PDFs.  We could surface the actual PDFs or try to work with Knowledge within Service Cloud.  But we can do better: Let’s actually surface the data within the PDFs in a very effective way through a chat interface to these customers.  Let’s let Agentforce work effectively with this unstructured data.

First a demo of how this works.

1. Here is our Agent who is ready to answer our questions.
   

   Agentforce Agent Ready

2. Here is our question: For a 2024 Ford F150 how do I make a warranty claim? 
3. Here is the answer from our Agent
   

   Agentforce Agent Answer

4. It worked!  How do I know that?  Because the answer came word for word from the PDF content that I had uploaded earlier.
5. Here is a piece of that FAQ document that exists as a PDF.
   

   FAQ Content

How was this solution built?

1. An Agentforce Data Library was built.
2. Go to Setup, Search for Agentforce Data Library
3. Click on ‘New Library’
   

   Create new Agentforce Data Library

4. Give it a Name, API Name and Description and click on Save.
5. Once you have your Agentforce Data Library you have to choose between leveraging Knowledge or File Uploads.  You cannot do both in the same Library.  In our example we are doing File Uploads.
6. We then upload whatever PDF files we want so the content can be used by your Agent. In this example I uploaded a couple of FAQ documents about vehicle warranty information.
   

   Upload Files to Library

7. At this point when the file uploads occur there is a lot happening for us automatically in the background in Data Cloud.  Salesforce has ingested that PDF, chunked it out and placed the content in some Data Cloud objects so it can be indexed and easily retrieved.
8. The base object showing that the file has been uploaded goes in the ‘DMO’ called ‘RagFileUDMO’.  You can view it in the ‘Data Explorer’ in Data Cloud.
   

   File level DMO in Data Cloud

9. There are two other objects where the ‘Chunks’ of data live.  When we did the File Upload into the Agentforce Data Library, Data Cloud automatically pulled the content out of the PDF, broke the text/content into ‘chunks’ and then put those ‘chunks’ of text/content into a DMO where it is indexed and made to be searchable.   There is a ‘SI_chunk’ and a ‘SI_index’ DMO.  Here is the ‘SI_chunk’ one…
   

   Search DMO in Data Cloud

10. There will be use cases where doing a manual load into an Agentforce Data Library would not be manageable or scalable, so there are integration options where files (Unstructured Data) could be loaded into Amazon S3, Azure Blog or GCP and then automatically pushed to Data Cloud.  We will save those steps for another blog post.
11. Now that the PDF content is ready to be used, we need to tell our Agent to use this specific Agentforce Data Library.  An Agent can only point at one Agentforce Data Library so it knows specifically where to look.
12. Open up your Agent by going to ‘Agents’ in Setup and then using the drop-down to the right of your Agent to choose ‘Open in Builder’.
13. Now select the Agentforce Data Library you have created after you select the Library ‘Book’ icon on the left.
    

    Agentforce Data Library

14. We now want to make sure that our Agent will use the ‘Answer Questions with Knowledge’ Action when the user prompts the Agent with questions about warranty.
15. In order to do this I created a new ‘Warranty FAQ’ Topic and gave it instructions and examples.
    

    Topic Configurations and Instructions

16. Then I made sure it has only one Action, which is the ‘Answer Questions with Knowledge’.  This out of the box Action will use the Library that is associated with this Agent.
    

    Topic Actions

17. Note that if I did not create this custom ‘Warranty FAQ’ Topic the Agent might default over to the ‘MigrationDefaultTopic’ Topic and not use the proper Action.
18. Building proper and detailed Instructions is very important within an Agent.
19. Remember that you can do a lot of great testing and see which Topics are Actions are being selected and executed within the Agent Builder.

That is it!

We have an Agent that can leverage PDF content that was created with ‘No Code’.  This solution is fully within the Trust architecture that Salesforce has in place for Agentforce. We needed the Agentforce Data Library, our PDFs, and a new Topic.  That is really it!

If you are brainstorming about use cases for Agentforce, please read on with this blog post from my colleague Darshan Kukde!

Here is another blog post where I discussed returning structured data instead of the unstructured data we talked about in this blog post.

If you want a demo of this in action or want to go deeper please reach out and connect!

Python Optimization: Improve Code Performance

# List (mutable)
my_list = [1, 2, 3]
# Tuple (immutable, faster)
my_tuple = (1, 2, 3)

# Slow list lookup (O(n))
numbers = [1, 2, 3, 4, 5]
print(3 in numbers)  # Yawn... Slow!

# Fast set lookup (O(1))
numbers_set = {1, 2, 3, 4, 5}
print(3 in numbers_set)  # Blink and you'll miss it! ⚡

# Generator (better memory usage)
def squared_numbers(n):
    for i in range(n):
        yield i * i
squares = squared_numbers(1000000)  # No memory explosion! 💥

# Inefficient
for i in range(10000):
    result = expensive_function()  # Ugh! Repeating this is a performance killer 😩
    process(result)

# Optimized
cached_result = expensive_function()  # Call it once and chill 😎
for i in range(10000):
    process(cached_result)

# Traditional loop (meh...)
squares = []
for i in range(10):
    squares.append(i * i)

# Optimized list comprehension (so sleek! 😍)
squares = [i * i for i in range(10)]

# Inefficient (Creates too many temporary strings 🤯)
words = ["Hello", "world", "Python"]
sentence = ""
for word in words:
    sentence += word + " "

# Optimized (Effortless and FAST 💨)
sentence = " ".join(words)

name = "Alice"
age = 25

# Old formatting (Ew 🤢)
print("My name is {} and I am {} years old.".format(name, age))

# Optimized f-string (Sleek & stylish 😎)
print(f"My name is {name} and I am {age} years old.")

import timeit
print(timeit.timeit("sum(range(1000))", number=10000))  # How fast is your code? 🚀

import cProfile
cProfile.run('my_function()')  # Find bottlenecks like a pro! 🔍

import sys
my_list = [1, 2, 3, 4, 5]
print(sys.getsizeof(my_list))  # How big is that object? 🤔

import gc
large_object = [i for i in range(1000000)]
del large_object  # Say bye-bye to memory hog! 👋
gc.collect()  # Cleanup crew 🧹

from multiprocessing import Pool

def square(n):
    return n * n

with Pool(4) as p:  # Use 4 CPU cores 🏎
    results = p.map(square, range(100))

import threading

def print_numbers():
    for i in range(10):
        print(i)

thread = threading.Thread(target=print_numbers)
thread.start()
thread.join()

The rapidly evolving payments industry is driving industry leaders to adapt their strategies in response to emerging trends. As technology advances and consumer expectations shift, staying ahead of these trends is crucial for success.

Payments Trend #1: AI-Driven Payment Innovations

The landscape of payments and financial services in 2025 will be marked by groundbreaking innovations and user-centric designs powered by Generative AI (GenAI). The industry faces numerous challenges, including protecting sensitive data, navigating evolving regulations, and outdated legacy systems. As these AI technologies evolve, they will transform consumer interactions with payment systems, fostering a more inclusive and sustainable financial ecosystem. This transformation will require a delicate balance between innovation and compliance, ensuring that advancements in AI contribute to a secure and efficient payments landscape.

Recommended Approach: GenAI can assist various payment processes by creating personalized and tailored payment experiences through loyalty programs, discounts, and curated product recommendations. Additionally, AI can enhance accessibility and mobile development through voice and conversational payments, improving user experience. The conversational nature of GenAI will be crucial in making transactions seamless and frictionless for consumers. To harness AI’s potential effectively, it’s essential to develop a strategy that considers payment regulations to ensure consumer protection, data privacy, and ethical use of AI. The future of payments promises not only enhanced efficiency and security but also personalized experiences that align with broader societal values.

Explore More: Transforming Industries, Powering Innovation

Payments Trend #2: The Rise of Real-Time Payments

Real-time payments in the US are expected to see widespread adoption across various sectors, driven by the integration of embedded finance, enhanced biometric authentication, and improved accessibility for consumers and businesses. Traditional payment methods like checks and ACH transfers are likely to decline, especially in business-to-business transactions. Consumers are increasingly using mobile wallets and embedded payments in non-financial platforms, while businesses are leveraging the momentum of business-to-business real-time payments facilitated by networks like FedNow. However, the payment industry encounters challenges such as user education and awareness, integration complexities across platforms and financial institutions, and ongoing regulatory considerations.

Recommended Approach: Payment companies should adopt and expand real-time payment solutions, leveraging networks like FedNow and RTP. Embracing advanced security features such as biometric authentication will enhance user experience and protect data. Ensuring inclusivity and accessibility for all consumers, including those underserved by traditional banking systems, is crucial. Additionally, businesses should explore new revenue models through premium features and address integration complexities with robust data governance and analytics. By focusing on these key areas, companies can effectively manage the challenges and opportunities presented by the widespread adoption of real-time payments.

Success In Action: Ensuring Interoperable, Compliant Real-Time Payments

Payments Trend #3: Navigating the New Regulatory Landscape

The payment industry faces drastic regulatory changes driven by the new administration. Ongoing changes to regulators, protocols, and best practices may have a lasting impact on nonbank financial companies (NBFCs), banks, fees, buy now, pay later (BNPL) services, payment apps, and digital wallets. These changes require significant adjustments in risk management, compliance frameworks, and operational protocols. Enforcing consumer protections will become a gray area, creating operational headaches for consumers and financial institutions. Additionally, the Consumer Credit Control Act (CCCA), currently under consideration, could have significant implications for payment providers. These regulatory changes impact banks and their third-party partners, requiring reassessment of partnerships and compliance strategies. Overall, companies need to adapt to these changes, leading to higher compliance costs, operational expense, and cultural shifts to thrive.

Recommended Approach:   To navigate these changes, businesses must balance innovation with compliance. AI will be pivotal in this transition, enabling automation of key compliance processes such as know your customer (KYC) and anti-money laundering (AML) checks. Additionally, AI’s capacity for real-time transaction monitoring and fraud prevention will help companies stay ahead of evolving regulatory demands.  The fintech industry, once celebrated for its agility and innovation, now faces a future shaped by heightened regulation. Leveraging AI-driven compliance solutions will be essential for managing global operations effectively in this increasingly complex landscape.

Related: 1033 Open Banking Mandate Blueprint for Success

Payments Trend #4: Optimizing Payment Orchestration Platforms

Payment orchestration platforms (POPs) are poised to play a critical role in the evolving payments landscape in 2025, driven by technological advancements, regulatory changes, and shifting consumer demands. The growth of cross-border transactions, fueled by global e-commerce expansion, necessitates platforms that can handle multiple payment methods, currencies, and compliance requirements. Advanced analytics and AI integration are becoming essential for improving transaction success rates, fraud detection, and overall business intelligence. Additionally, regulatory developments will shape the operation of POPs, aiming to enhance security and reduce fraud. Emerging regions like Asia-Pacific, Africa, and Latin America are key growth areas, with partnerships enabling access to local payment methods.

Recommended approach: To navigate this trend, payment institutions should focus on several strategies. POPs market consolidation is leading to more robust, full-stack solutions that integrate orchestration capabilities into broader platforms. Embracing advanced analytics and AI tools will be crucial for optimizing payment processes and enhancing customer experiences. Institutions should also prioritize the implementation of smart checkout experiences to improve authorization rates and streamline payment options. Staying up to date with regulatory developments and ensuring compliance with new regulations like the third(PSD3) in the EU and the role of central bank digital currencies (CBDCs) will be essential. Finally, integrating POPs with existing financial services and e-commerce platforms will modernize legacy systems and provide more seamless payment experiences, ensuring institutions remain competitive in the digital economy.

Success In Action: At the Heart of Financial Services

Payments Trend #5: The Rapid Adoption of Embedded Payments

Embedded payments are rapidly evolving, and 2025 will mark a major turning point for their adoption in the U.S. Businesses and consumers demand faster, more seamless transactions, driving the expansion of embedded payment solutions across industries. While e-commerce and fintech have been early adopters, industries such as healthcare, manufacturing, real estate, and B2B services are now integrating payment capabilities directly into their platforms. Expect more ERP systems, procurement platforms, and business management tools to embed payment functions, reducing reliance on third-party processors. As embedded payments become mainstream, U.S. regulators will tighten compliance requirements around data security, AML, and consumer protection.

Recommended Approach: Companies must meet evolving KYC and compliance standards, fostering trust and security in digital transactions. Beyond payments, businesses should integrate lending, insurance, and investment options directly into their platforms through embedded finance. Partnering with Banking as a Service (BaaS) providers will allow companies to offer customers seamless access to financial products without switching platforms, further blurring the lines between traditional banking and digital platforms. Additionally, adopting tokenized payments, stablecoins, and decentralized finance (DeFi) integrations within embedded payment systems will be crucial. With Apple Pay, Google Pay, and PayPal leading the charge, expect an increase in one-click, biometric, and voice-activated payments built into everyday digital experiences. Companies that fail to integrate seamless payment experiences risk losing customers to competitors offering faster, frictionless transactions.

You May Also Enjoy: Getting Started On Embedded Finance

Payments Trend #6: Crypto and Payments Intersect

In 2024, crypto made a strong comeback, with Bitcoin surpassing $100,000, driven by its integration into exchange-traded funds. The industry has matured, with blockchain innovations extending beyond crypto enthusiasts and into mainstream finance. Traditional financial institutions are increasingly leveraging blockchain to address complex challenges, while the U.S. continues efforts to regulate and integrate digital assets effectively. Emphasis on security, trust, and usability is essential for blockchain’s success. With these elements in place, financial institutions are embracing blockchain-based solutions, including tokenized money and assets, to enhance efficiency and reduce costs.

Recommended Approach: Companies should explore the coexistence of stablecoins and tokenized deposits. Banks are investigating tokenized deposits, blockchain-based representations of commercial deposits, to enable faster settlements and programmable payments. Meanwhile, stablecoins, pegged to fiat currency, are gaining traction in remittances and business transactions, with approximately $150 billion in circulation. A clear regulatory framework will strengthen their role, leading to an integrated system where tokenized assets and money interact seamlessly. Regulatory clarity will drive adoption, with the U.S. and EU providing models for certainty. Central banks focus on blockchain solutions for financial institutions, enhancing institutional settlements and facilitating faster cross-border capital movement. Interoperability and trust will be crucial, with institutional interest in crypto growing. The future of crypto is no longer speculative, it is becoming a fundamental part of the financial system.

See Also: Be at the Forefront of Innovation

Navigating the Road Ahead

We help payment and fintech firms innovate and boost market position with transformative digital experiences and efficient operations.

• Business Transformation: Create a roadmap to innovate products, enhance experiences, and reduce transactional risk.
• Modernization: Implement technology to improve payment processing, fraud management, and omnichannel experiences.
• Data + Analytics: Proactively leverage integrated data and AI to optimize transactions, manage fraud, and personalize experiences.
• Risk + Compliance: Enhance compliance and risk management to safeguard transactions and customer data.
• Consumer Experience: Deliver convenient, seamless experiences with user-friendly secure payment solutions.

Discover why we have been trusted by 25+ leading payments and card processing companies. Explore our financial services expertise and contact us to learn more.

AI is no longer a futuristic concept—it’s here, transforming the way we work in real time. Organizations worldwide making AI a strategic priority, harnessing its power to enhance efficiency, accelerate decision-making, and drive growth. In fact, generative AI adoption has skyrocketed from 55% in 2023 to 75% in 2024, contributing to an estimated global economic impact of $19.9 trillion. To stay ahead, businesses must align AI investments across applications, platforms, data, and infrastructure to maximize value and maintain a competitive edge.

Watch our latest video to see Microsoft Copilot in action and how AI is reshaping workflows across every role.

“In the evolving landscape of AI, the future hinges on our ability to not just experiment, but to strategically pivot—transforming experimentation into sustainable innovation,” said Rick Villars, group vice president, Worldwide Research at IDC. “As we embrace AI, we need to prioritize relevance, urgency, and resourcefulness to forge resilient enterprises that thrive in a data-driven world.” 

Success with AI isn’t just about adopting new technology—it requires a clear vision, a strong strategy, and the right expertise to turn possibilities into real-world impact. As a Microsoft partner, Perficient is at the forefront of AI transformation, helping businesses navigate this evolving landscape. Our upcoming Microsoft Copilot video showcases exactly how AI is reshaping everyday workflows, with real-world examples of how different roles—from executives to developers—are leveraging Copilot to work smarter and more efficiently. The world is changing, and AI is advancing at an unprecedented pace. Now is the time to lead, innovate, and unlock the full potential of AI in your organization.

Microsoft Copilot: The AI-Powered Workplace Ally 

Microsoft Copilot is an AI-powered assistant designed to enhance productivity across Microsoft applications and services. It leverages advanced language models and integrates seamlessly with Microsoft 365, Dynamics 365, and GitHub to provide real-time assistance, automate tasks, and offer intelligent suggestions. 

Key Features:

• Content Generation: Drafts emails, documents, and presentations with contextually relevant suggestions.
• Data Analysis: Helps interpret data in Excel, offering insights and generating summaries for better decision-making.
• Meeting Summaries: Provides concise overviews of meetings, highlighting key points and action items.
• Code Assistance: Supports developers by suggesting code snippets and completing code blocks in GitHub.

Microsoft Copilot uniquely integrates web intelligence, organizational data, and user context to provide powerful assistance. It enhances workflows across roles—from sales teams managing customer interactions, to HR professionals optimizing employee support, to developers accelerating coding projects. With privacy and security at the forefront, Copilot empowers every end user to work smarter and achieve more. 

Real-World AI Impact: How Businesses Are Using Microsoft Copilot

Organizations are leveraging Copilot to streamline operations, enhance productivity, and drive business success. Here are the top use cases where our clients and prospects see the most value: 

• Company Executives: Leveraging AI-driven insights to make informed strategic decisions and improve business performance.
• Customer Service Teams: Enhancing response times and preemptively resolving issues with predictive AI.
• HR Professionals: Automating policy updates, employee inquiries, and streamlining workforce management.
• Legal & Operations: Simplifying contract reviews, compliance tracking, and change management processes.
• Sales Reps: Accessing deep customer insights, automating CRM updates, and optimizing meeting preparation.
• Developers: Speeding up application development with AI-assisted code suggestions and debugging support.

Each of these use cases is explored in depth in our Microsoft Copilot video, where we demonstrate real-world applications of AI across various industries and roles.

The Future of AI-Powered Workflows

The next phase of AI transformation will continue to reshape industries. As Microsoft’s Chairman and CEO Satya Nadella explains, “2025 will be about model-forward applications that reshape all application categories. More so than any previous platform shift, every layer of the application stack will be impacted. It’s akin to GUI, internet servers, and cloud-native databases all being introduced into the app stack simultaneously. Thirty years of change is being compressed into three years!” 

Key advancements to watch:

• Agentic AI: AI applications will develop memory, entitlements, and action spaces, allowing them to perform complex tasks independently.
• The End of the SaaS Age: AI agents will replace traditional SaaS models, integrating multiple platforms and automating workflows.
• CoreAI Initiative: Microsoft’s CoreAI unit is driving next-gen AI capabilities, streamlining platforms, and enhancing AI-driven applications.

Partnering With Perficient for AI Transformation

Perficient and Microsoft can help your organization confidently scale AI solutions, no matter where you are on your AI journey. Our Microsoft AI solutions are designed to unlock new levels of productivity, drive innovation, fuel growth, and ensure secure AI integration across all business functions. Let’s shape the future together. Read more about our Copilot and AI capabilities here.