The relationship between Quality Assurance (QA) and Software Development teams is often marked by tension and conflicting priorities. But what if this friction could be the spark that ignites innovation and leads to unbreakable products? 

The Power of Productive Tension 

It’s no secret that QA and Development teams sometimes clash. QA and testing professionals are tasked with finding flaws and ensuring stability, while developers are focused on building features, focusing on speed and innovation. This natural tension, however, can be a powerful force when channeled correctly. 

 One of the key challenges in harnessing this synergy is breaking down the traditional silos between QA and Development and aligning teams early in the development process. 

1. Shared Goals: Align both teams around common objectives that prioritize both quality and innovation.
2. Cross-Functional Teams: Encourage collaboration by integrating QA professionals into development sprints from the start.
3. Continuous Feedback: Implement systems that allow for rapid, ongoing communication between teams.

 Leveraging Automation and AI 

Automation and artificial intelligence are playing an increasingly crucial role in bridging the gap between QA and Software Development Teams: 

1. Automated Testing: Frees up QA teams to focus on more complex, exploratory testing scenarios.
2. AI-Powered Analysis: Helps identify patterns and potential issues that human testers might miss.
3. Predictive Quality Assurance: Uses machine learning to anticipate potential bugs before they even occur.

 Best Practices  

Achieving true synergy between QA and Development isn’t always easy, but it’s well worth the effort. Here are some best practices to keep in mind: 

1. Encourage Open Communication: Create an environment where team members feel comfortable sharing ideas and concerns early and often.
2. Celebrate Collaborative Wins: Recognize and reward instances where QA-Dev cooperation leads to significant improvements.
3. Continuous Learning: Invest in training programs that help both teams understand each other’s perspectives and challenges.
4. Embrace Failure as a Learning Opportunity: Use setbacks as a chance to improve processes and strengthen the relationship between teams.

As business leaders are tasked with doing more with less, the relationship between QA and Development will only become more crucial. By embracing the productive tension between these teams and implementing strategies to foster collaboration, organizations can unlock new levels of innovation and product quality. 

Are you ready to turn your development and testing friction into a strategic advantage?

Artificial intelligence (AI) is transforming the way businesses operate across various domains and functions. From retailers improving their customer experience to marketers finding time and cost savings with generated content, we believe that AI has the power to improve organizations of industries. One of the areas where AI can have a significant impact is financial planning and analysis (FP&A), a core function of the finance department that involves forecasting, budgeting, reporting, and decision support. In this blog post, we will explore how finance leaders can leverage AI, especially machine learning, to improve the efficiency and accuracy of FP&A processes, and how they can get started with AI integration. 

Why Artificial Intelligence for FP&A? 

Machine learning is a branch of AI that uses statistical models to learn from data and make predictions. Machine learning can be applied to FP&A tasks such as revenue forecasting, expense planning, cash flow analysis, and scenario modeling. By using machine learning, finance leaders can: 

• Automate tedious and manual tasks, such as data collection, consolidation, and validation, and free up time for more strategic and value-added activities. 
• Enhance the quality and reliability of forecasts, by incorporating more data sources, detecting patterns and trends, and reducing human errors and biases. 
• Gain deeper insights and actionable recommendations, by exploring what-if scenarios, identifying drivers and risks, and optimizing resource allocation. 

Machine learning is not a replacement for human judgment and expertise, but rather a powerful tool that can augment and complement the existing FP&A capabilities. Machine learning can help finance leaders to deliver more timely, accurate, and relevant information to support business decisions and performance management.  

What are the Market Trends and Opportunities? 

According to a recent Gartner report1, AI is one of the top priorities for CFOs and finance leaders in 2024, as they seek to improve operational efficiency, enhance business agility, and drive digital transformation. However, the adoption of AI in finance is still relatively low, compared to other functions such as marketing, sales, and customer service. This means that there is a huge opportunity for finance leaders to gain a competitive edge by embracing AI and machine learning in their FP&A processes. 

One of the key challenges that finance leaders face when adopting AI is the lack of technical skills and knowledge. Many finance professionals may feel intimidated or overwhelmed by the complexity and variety of AI and machine learning techniques and tools. However, as the technology matures and becomes more accessible, finance leaders do not need to be AI or machine learning experts to utilize them effectively. There are many solutions and platforms available that can simplify and streamline the AI integration process, such as Perficient’s Performance Intelligence Solutions2, which enable finance leaders to leverage machine learning for FP&A without requiring extensive coding or data science skills. 

How to Get Started with AI Integration?

The best way to get started with AI integration in FP&A is to start small and think big. Finance leaders should identify a specific use case or problem that can be solved or improved by using machine learning, such as revenue forecasting, expense planning, or cash flow analysis. Then, they should select a suitable machine learning model or technique, such as regression, classification, or clustering, and apply it to a subset of data to test and evaluate its performance. By using a data-driven and iterative approach, finance leaders can measure the impact and ROI of machine learning, such as the improvement in forecast accuracy, the reduction in forecast cycle time, or the increase in forecast confidence. They can also compare the machine learning results with the traditional methods, such as Excel spreadsheets or statistical models, and demonstrate the value and benefits of machine learning to the key stakeholders. 

Once the initial use case or pilot project is successful, finance leaders can scale up and expand the scope of AI integration, by incorporating more data sources, more machine learning models, and more FP&A tasks. They can also explore other advanced applications of AI, such as natural language processing, computer vision, or generative AI, to further enhance their FP&A capabilities and outcomes. 

Conclusion 

AI integration is not a futuristic or optional endeavor for finance leaders, but a strategic and imperative one. By using AI, especially machine learning, finance leaders can transform their FP&A processes from being reactive and descriptive, to being proactive and prescriptive. They can also gain a competitive advantage and drive business value by delivering more accurate, timely, and relevant information and insights to support business decisions and performance management. To achieve this, finance leaders should start small and think big, and leverage the available solutions and platforms that can simplify and streamline the AI integration process. 

 How AI and Automation are Changing the Retail Game

As the digital landscape continues to evolve, retailers are increasingly turning to AI and automation to gain a competitive edge. Forrester interviewed Perficient for its recent report The Forrester Tech Tide: Retail AI And Automation, Q1 2024 , and listed Perficient among sample vendors for Digital Experience Optimization. According to the report, “AI and automation are increasingly critical to retail firms’ ability to win, serve, and retain their customers,” and the report analyzes the importance of these technologies in retail initiatives.

The Retail Imperative: AI and Automation

In today’s hyper-competitive retail environment, companies must navigate a complex web of customer expectations, supply chain challenges, and operational efficiency. Enter AI and automation, two powerful tools that can transform the retail landscape. Here’s why they matter:

• Winning Customers: AI-powered personalization, chatbots, and recommendation engines enhance the customer experience. By understanding individual preferences and behavior through AI and automation tools, retailers can tailor offerings, drive conversions, and foster loyalty with consumers.
• Serving Efficiently: Automation streamlines processes across the retail value chain. From inventory management to order fulfillment, smart algorithms help optimize operations, reduce costs, and improve speed.
• Retaining Loyalty: Predictive analytics and AI-driven insights enable retailers to proactively address customer needs. Whether it’s replenishing stock or suggesting complementary products, these technologies enhance long-term relationships.

According to the report, “GenAI exhibits great promise but risks confusion” in transforming the retail industry, while currently, “The MVPs of retail AI and automation are some of the oldest solutions.”

Navigating AI and Automation Technologies in The Forrester Tech Tide

The Forrester report explores “Sixteen Technologies [that] Underpin Growth” in retail. Two areas of focus that Perficient helps retailers with are Digital Experience (DX) Optimization and Generative AI implementation.

Digital Experience (DX) Optimization: In today’s hyper-connected world where customers can begin a shopping spree on one device, checkout on another, and pick up in person or request delivery, a seamless and agile digital experience is non-negotiable for retailers. DX optimization contributes to organizational success in a number of ways, and we believe Perficient’s contributions to retailers has allowed us to be listed among DX Optimization sample vendors in Forrester’s Tech Tide.

According to Forrester, “Digital experience (DX) optimization solutions leverage recommendation, testing, and personalization engines as well as other operations inputs such as inventory availability, weather, day part, shopper preferences, demographics, or retail media availability to optimize the shopper’s experience across touchpoints and to reduce costs.” We believe Perficient consistently helps brands enhance their commerce capabilities and deliver immersive and hyper-personalized experiences with the use of innovative AI and automation implementation. Namely, retailers can delight shoppers with features like AI-driven search, mobile payments, virtual product experiences, and product education.

Generative AI: As retailers navigate the intricacies of today’s dynamic market landscape, the integration of generative AI emerges as a pivotal strategy in enhancing customer engagement and operational efficiency. Forrester underscores the significance of generative AI in reshaping retail dynamics, stating, “The biggest use cases for genAI in retail are chatbots, generative code and code copilots, and text and images to support marketing…All of these solutions exhibit promise in their ability to reduce retailer costs by improving operational efficiencies.”

This technology not only enables retailers to craft compelling narratives but also facilitates personalized interactions that resonate with diverse consumer segments. With its potential to revolutionize content creation and campaign optimization, we believe the integration of generative AI stands as a cornerstone in Perficient’s commitment to empowering retailers with cutting-edge solutions for sustained market relevance and customer satisfaction.

We’ve helped many organizations, including a large automotive company, integrate chatbots and virtual assistants to make their website more user friendly, improve the customer experience, and ultimately to drive sales. Learn more about how we are utilizing NLP-powered chatbots to drive customer experiences.

Putting Insights Into Action

As a digital business professional, how can you leverage the Forrester Tech Tide insights? Consider the following steps:

1. Assess Maturity: Evaluate where your organization stands in adopting AI and automation technologies. Are you an early adopter or catching up?
2. Prioritize Investments: Based on the report’s maturity assessment of each technology, prioritize investments to allocate resources in areas that promise maximum impact.
3. Collaborate Across Functions: AI and automation transcend silos. Involve marketing, operations, and IT teams to create a holistic strategy.
4. Stay Agile: The retail landscape evolves rapidly. Be prepared to adapt as new technologies emerge.

The Forrester Tech Tide report is a compass for retail leaders navigating the AI and automation landscape. As you shape your investment approach, remember that bold decisions lead to customer-centric success. Unlock growth, serve efficiently, and retain loyalty—powered by AI and automation. Read the full report here (available to Forrester subscribers and for purchase).

Revolutionizing B2C Commerce: The Impact of Generative AI

In the dynamic landscape of commerce and consumer-driven markets, Business-to-Consumer (B2C) organizations are increasingly turning to generative AI to revolutionize their operations and enhance customer experiences. Generative AI, a subset of artificial intelligence, empowers these organizations to create content, personalize interactions, and optimize various aspects of their business processes. By leveraging advanced algorithms and machine learning models, B2C companies can now tailor their offerings to individual preferences, predict consumer behavior, and streamline the overall customer journey.

This transformative technology not only enables unprecedented levels of personalization but also contributes to improved efficiency, cost-effectiveness, and competitiveness in an ever-evolving marketplace. In this era of digital innovation, the strategic integration of generative AI has emerged as a key driver for B2C organizations seeking to stay ahead of the curve and deliver unparalleled value to their customers.

In its recent report, How Generative AI Is Changing The Game In B2C Commerce Solutions, Forrester states, “To better understand genAI’s role in commerce tech solutions, we launched a research series where we ask leading vendors to outline how they’re bringing genAI into their products today.” Perficient’s Commerce and Generative AI experts were interviewed by Forrester to discuss our perspective of genAI in commerce solutions, and Perficient is listed as a company interviewed for this report.

Generative AI at Perficient

From chatbots to intelligent document automation, Perficient is helping organizations utilize AI and generative AI to streamline business processes and improve the customer experience. We have a Generative AI Innovation Group (IG) that is comprised of hundreds of Perficient strategists, designers, and developers from around the world with an interest and expertise in new technologies to discuss applications and opportunities for the market. This group drives innovation, connection, and community with Perficient’s clients, colleagues and partners, about the emergence of generative AI tools and capabilities, and the impact these technologies will have on businesses. The group also identifies and develops market offerings, internal use cases and applications, and routinely hosts events that educate, enable, and engage colleagues about the groundbreaking technology and its implications for transforming enterprise operations.

Generative AI is a rapidly evolving area of artificial intelligence that’s driving a new wave of digital transformation, and we’ve outlined below how Perficient is helping B2C organizations harness this power in a multitude of ways.  

How Generative AI Can Enhance Your Commerce Solutions

From image and video synthesis to natural language processing and beyond, generative AI solutions are becoming an essential part of business. At Perficient, we want to first explore the business challenges in order to validate potential outcomes and optimization solutions.

Unified commerce takes the customer experience a step further, and is essentially the ability to have an ongoing digital dialogue that curates enhanced customer lifetime value and brand affinity. By utilizing AI and Machine Learning (ML), organizations are able to better understand and communicate with their customers and offer them a more targeted and personalized experience. In the report, Forrester states, “Half of the vendor respondents noted that using genAI to deliver more effective promotions was on their radar. Specific use cases are autogenerated custom promotions across email, SMS, and messaging apps, as well as leveraging segmentation and analytics to deliver more personalized offers,” which we believe ties into unified commerce.

On top of personalizing experiences, AI can help generate marketing content (in multiple languages), provide appropriate tagging, aid in guided selling, and help even in the contact center space with chatbots.

From AI-generated content to guided selling and customer service, generative AI is an important technology for B2C commerce organizations to utilize.

Experts in Commerce and AI

Forrester interviewed leaders from Perficient’s Commerce and Artificial Intelligence Practices while conducting research for this report. Perficient is excited to continue sharing thought leadership and perspective on emerging trends in this space as we work toward our goals of helping our clients meet their customers and employees where they are in the B2C space. To learn more, download How Generative AI Is Changing The Game In B2C Commerce Solutions, available to purchase or to Forrester subscribers, today.

In today’s rapidly evolving digital landscape, the promise of Generative Artificial Intelligence (GenAI) looms large, offering enticing opportunities for innovation, efficiency, and growth. However, alongside its transformative potential, AI brings with it a host of complexities and challenges that can give even the most seasoned executives pause.

A majority of organizations are not fully embracing GenAI. This reluctance stems from a variety of concerns, including alignment issues within leadership teams, uncertainty regarding AI’s practical applications, and a lack of clarity on how to effectively integrate and implement generative AI technologies.

These apprehensions are not unfounded. The landscape of AI is fraught with potential pitfalls, ranging from ethical dilemmas and regulatory compliance to technical complexities and cultural resistance. Moreover, the sheer pace of technological advancement can often leave decision-makers feeling overwhelmed and uncertain about how best to navigate this new frontier.

The PACE Engagement Model

Our PACE framework provides a holistic approach to responsibly operationalizing AI across an organization. ​It empowers organizations to unlock the benefits of AI while proactively addressing risks. PACE addresses the key factors in responsible GenAI adoption, including company Policies, Advocacy, Controls, and Enablement.

But our PACE framework is more than just a guideline; it’s a strategic blueprint for organizations embarking on their AI journey. In an era where AI’s impact is profound and far-reaching, PACE ensures that AI solutions are not only innovative but also ethical, compliant, and effective.

Our PACE engagement model is broken into three steps:

• Evaluate the Landscape: Our journey with AI begins with a thorough evaluation. Understanding the current AI capabilities, stakeholder needs, and the balance of risks and opportunities is crucial. This step ensures that AI initiatives align with the organization’s objectives and are poised for success.
• Define the Standards: The second step is where the PACE framework truly shines. By establishing robust policies and standards, organizations create a strong foundation for responsible AI usage. Training and advocacy are integral at this stage, ensuring that every team member understands and champions the ethical use of AI. Control mechanisms like risk assessments and quality checks are essential safeguards, ensuring AI solutions are reliable and trustworthy.
• Deploy Across the Enterprise: The final step is the practical application of AI across the organization. This involves setting up the necessary infrastructure, integrating AI into business processes, and, importantly, establishing a culture of continuous improvement. The “Review and Refine” phase is not just about maintaining standards; it’s about evolving and enhancing AI capabilities over time.

Why Operationalize AI Now?

As organizations look to remain competitive and relevant in a rapidly evolving digital landscape, embracing GenAI isn’t just an option; it’s a necessity for staying ahead of the curve and driving innovation. By leveraging the transformative power of AI responsibly, organizations can unlock new opportunities, streamline operations, and deliver enhanced experiences for customers and stakeholders alike. The PACE framework serves as a guiding light in this journey, helping organizations navigate the complexities of AI adoption with confidence and clarity, ensuring they remain at the forefront of technological innovation and ethical leadership.

Adoption and change is going to happen, whether governed or not. User expectations and behaviors are actively shifting – as individuals, as consumers, as workers. Learn more about how Perficient can help your organization harness the power of this technology- contact us today.

As we step into 2024, the transformative impact of Artificial Intelligence (AI) and generative AI on enterprise-level organizations has reshaped the business landscape in profound ways. The continual evolution of these technologies has empowered businesses to leverage advanced algorithms, predictive modeling, and generative capabilities, driving unprecedented innovation and efficiency. From enhancing decision-making processes to revolutionizing customer interactions, the influence of AI has positioned enterprises at the forefront of a dynamic digital era, where adaptability and integration of cutting-edge technologies are paramount for sustained success.

However, adopting AI at an enterprise level is not without its challenges, given the complexities of integration and optimization within existing frameworks. Navigating this landscape is made significantly more manageable with the assistance of a specialized consulting partner well-versed in AI. Such expertise ensures a strategic and tailored approach, enabling organizations to overcome obstacles, unlock AI’s full potential, and thrive in the dynamic business environment of 2024.

The AI Services Landscape, Q1 2024

The recently published AI Services Landscape, Q1 2024 report by Forrester states that “Generative AI (genAI) created an AI awakening among business stakeholders and workers.” The business value of implementing AI initiatives in partnership with AI service providers can be significant, and that’s why we’re proud to be recognized in the Forrester AI Services Landscape as a service provider with an industry focus in the sectors of Pharmaceutical and medical equipment, Transportation, and Financial services, and a geographic focus in North America, Asia Pacific, and Latin America.

Our AI Capabilities

Forrester carefully researched each service provider in the report through a set of comprehensive questions and identified three core business scenarios – customer experience, process automation, and edge intelligence. According to Forrester, “These are the business scenarios that buyers most frequently seek and expect AI services providers to address.” We believe as a leading digital consultancy that helps clients imagine, create, engineer, and run digital transformation and AI solutions, we in turn, help organizations drive growth, efficiency, and differentiation in these three areas.

One of the ways we help organizations optimize their customer journeys is through our CX AI Jumpstart, a 5 week approach to identifying and implementing AI opportunities. Built on our accelerated modeling process, CX AI focuses on developing an interactive model that demonstrates how your organization can leverage machine learning, natural language processing, and cognitive computing to jump start Al adoption.

In addition to the core business scenarios in this report, Forrester also references seven extended business scenarios that are important to certain buyers looking for artificial intelligence implementation services.

Forrester asked each vendor included in the Landscape to select the top business scenarios for which clients select them and from there determined which are the extended business scenarios that highlight differentiation among the vendors. We are shown in the report for having selected Product and service development, Knowledge management, and Content creation as some of the top reasons clients work with us out of the listed extended business scenarios.

Learn More About Perficient’s AI Services

Whether your business is just starting its AI journey or seeking to enhance its current efforts, partnering with the right service provider can make all the difference. With a team of more than 300 AI professionals, including data scientists, data engineers, AI architects, and AI developers, Perficient has extensive knowledge and skills in various AI domains. Contact us now to discover how our expertise can take your business to new heights.

Download the Forrester report, The AI Services Landscape, Q1 2024 to learn more (available to Forrester subscribers and for purchase).

In the fast-paced landscape of today’s business environment, organizations are constantly evolving to meet the ever-changing needs of their customers. However, the traditional Customer Relationship Management (CRM) systems that once served as the backbone for managing customer data and interactions are now struggling to keep up. Recently, Perficient hosted a roundtable discussion with marketing leaders from some of the top organizations from various industries. During this event, we dove into the challenges organizations face with their CRM systems and explored the need for a modern customer data strategy.

The Overgrown CRM:

Many organizations find themselves outgrowing their CRM platforms, realizing that the one-size-fits-all approach no longer suffices for the complexities of modern customer data management. As CRM software expanded into vast data management platforms encompassing marketing, sales, and service, it lost its initial focus. The result is a cumbersome system that fails to cater to the specific needs of its core users – a classic case of trying to do too much.

Key Insights from Marketing Leaders

Our focus group with marketing leaders revealed crucial insights into the evolving landscape of customer data management.

1. Prioritizing Existing Customers:
   • In light of technological advancements and rising customer acquisition costs, organizations are shifting their focus towards existing customers.
   • This shift necessitates a reevaluation of how customer data is managed, moving beyond the traditional CRM model.
2. Identifying Priorities for Successful Implementation:
   • Successful Customer Data 360 implementation hinges on identifying and prioritizing key areas of focus.
   • Organizations grapple with a wealth of data and struggle to determine where to start; a strategic approach is crucial.
3. High Value Use Cases for Buy-In:
   • Gaining upper-level buy-in is a common challenge, but focusing on high-value use cases can justify project costs.
   • Organizations are finding success by demonstrating tangible benefits in specific areas before scaling up.
4. Product vs. Project Approach:
   • Adopting a Product vs. Project approach has proven to be successful.
   • Organizations are recognizing the need for continuous, iterative improvements over time rather than one-off projects.
5. Acquiring Executive Buy-In:
   • To secure executive support, organizations should focus on small, product-driven iterations that deliver quick successes.
   • Proving the value of a Customer Data 360 strategy through tangible outcomes is essential for garnering support.
6. Alignment with Business Goals:
   • Alignment with executive business goals is critical to providing downstream value for customer 360 initiatives.
   • Listening to customer feedback and aligning strategies accordingly ensures that the initiatives remain relevant and effective.

As organizations navigate the complexities of the modern business landscape, the era of all-encompassing CRM systems is giving way to a more nuanced and strategic approach to customer data management. By heeding the insights from marketing leaders and adopting a modern customer data strategy, organizations can ensure that they are not only meeting the needs of their customers but also staying ahead in a rapidly evolving marketplace. The key lies in agility, alignment with business goals, and a relentless focus on delivering value throughout the entire customer journey. It’s time to move beyond the CRM era and embrace a more dynamic and responsive approach to customer data.

Perficient is proud to announce our partnership with Writer, the AI platform built for the enterprise. This partnership will help accelerate our AI efforts by leveraging Writer’s capabilities to create content more efficiently and support our clients. This partnership will also accelerate Perficient clients’ use of generative AI, and empower them to create content efficiently and safely.

Writer is the only enterprise AI platform that builds off of LLM “clay,” adding layers of intelligence that include great writing, business context, your content, and your company facts.

Here are a few such capabilities, and how they enable Perficient to create content efficiently and safely in the age of generative AI:

Connect to data sources

With Knowledge Graph, Writer snaps into your data sources, such as your wiki, cloud storage, chat channels, and knowledge bases, and acts as a source of truth to fact-check claims, do research, and ask questions in real time.

Govern your brand

Perficient trains Writer on clients’ brand, including your best content, voice, style guide, key terms, and core messages, so your AI-generated content is always on-brand.

Ensure security

Unlike other AI platforms, Writer won’t use your data in their models. Writer is compliant with SOC 2 Type II, PCI-DSS, HIPAA, GDPR, and Privacy Shield.

Your data will never make it into our machine learning models: your data is analyzed transiently, so what you edit or generate isn’t collected or used by Writer. Writer is compliant with the latest privacy and security standards, so you can confidently deliver secure customer experiences at scale.

Perficient and Generative AI

Brian Flanagan, AI Strategist spearheading Perficient’s Generative AI Practice, expressed his enthusiasm about the partnership and its potential impact on businesses worldwide: “At Perficient, we constantly strive to be at the forefront of technological advancements that empower our clients and enhance their digital experience. Our partnership with Writer AI represents an exciting leap forward in content generation, enabling us to deliver bespoke solutions to our customers that effortlessly combine human creativity with AI-powered efficiency.

Through this collaboration, Perficient will harness the true potential of generative AI, transforming how businesses approach content creation and customer engagement. Writer AI’s state-of-the-art platform complements our strategic vision, and we look forward to empowering enterprises with unparalleled content generation capabilities, elevating their brand presence and driving business growth.”

With Writer, Perficient can partner with our clients to create innovative content with speed and accuracy. This partnership will further Perficient’s edge in the competitive consulting landscape, showcasing our forward-thinking tech solutions to our clients via our Generative AI Innovation Lab. Our team is committed to making our clients successful with generative AI, and to providing the best possible solutions to your data and AI-related needs. Click here to learn more about our continued investment in Artificial Intelligence.

About Writer

Writer is the generative AI platform for enterprises. We empower your people — marketing, support, product, HR, and more — to maximize creativity and 10x productivity.

Our secure platform snaps easily into your business data sources and delivers accurate content that’s fine-tuned on your brand, messaging, and facts. We put generative AI in people’s hands right where they work, and enable you to build it into your end-user applications, without putting your or your users’ data at risk.

Writer is enterprise-grade and doesn’t use or share your data. We’re compliant with SOC 2 Type II, GDPR, HIPAA, and PCI, and are deployed at leading enterprises, including Intuit, UiPath, Spotify, L’Oreal, Uber, UnitedHealthcare, HubSpot, and Deloitte. Visit us at writer.com.

In the past 12 months, Artificial Intelligence has gone from a future technology that has the potential to be revolutionary to a must have to remain competitive. From August 2022 to August 2023, “How to use AI” has skyrocketed on Google Trends by 507% with many leading innovators believing that this is the next internet boom. With the proliferation of AI disrupting every industry, AI adoption is vital for organizations that wish to remain viable and competitive. The question we hear, though, is “how and where?”

This week, the Perficient Team headed to New York City with our Partners at Writer, the generative AI platform for enterprises. We met with Fortune 100 organizations to converse around AI and help begin to answer the question of “How and Where?” As pioneers in the space, our goal as partners is to work with clients to find quick and easy ways to begin implementing AI, and while we recognize most organizations are not NYC local, we are excited to share our key insights.

Generative AI Lessons Learned

Think transformational, not incremental

It’s important to get buy in early- begin to introduce AI with use cases that matter most to leadership. By making the first use cases transformational, not incremental, AI implementation will be adopted more readily and the value in the technology will be recognized.

Get out of the sandbox and solve real problems

For the solutions to have impact, the problems can’t be abstract. Move beyond proof-of-concepts to build real applications at scale with actual end users. While there are many hypothetical use cases of ways AI could be applied, leadership buy in is vital and showing real business and/or customer outcomes emphasizes the value and will help you move quicker.

Think cross-functionally

…but don’t get lost in Center of Excellence land. A cross-functional approach is needed, but avoid getting bogged down in CoEs.

Don’t rebuild the wheel in the quest to gain skills

Many organizations believe that fully custom technology is needed. By focusing on applying platforms that can fit your business needs versus rebuilding them from scratch, you can gain AI skills and benefits with speed and efficiency.

Identify all the business impact

Identify concrete ROI – Cost savings, incremental revenue, reduced legal and compliance risks. AI can impact many key metrics, and showing the holistic impact increases organizational adoption.

Adoption matters

While it’s important to get executive buy-in, the purpose of an AI implementation is to have real outcomes. Real outcomes require genuine end-user adoption.

Trends and Implications

• The pace of change is accelerating: We are entering an era of mass innovation, which is driving constant change. For organizations to stay innovative and competitive, they must begin to adopt new technology.
• AI is accessible to everyone: User expectations are being influenced by their experiences with Generative AI agents like ChatGPT, Bing and Bard.
•  Workers are adapting: 61% of US workers are either using or planning to use Generative AI to help them with their jobs.
• The hype is peaking: We are reaching the height of expectations for Generative AI.
• …but commercial adoption is lacking: Most organizations aren’t leveraging Generative AI as much as they would like.
• Computing resources are in high demand: Within the next 5 years, processing workloads are expected to increase by 50 times.

Operationalizing Generative AI

As organizations embark on their journey, they need a holistic approach to operationalizing Generative AI. Perficient’s P.A.C.E. framework offers a comprehensive strategy:

• Policies: Establishing corporate guidelines and boundaries for acceptable AI usage as new solutions emerge.
• Advocacy: Promoting the understanding and adoption of AI through continuous education and collaboration.
• Controls: Implementing the necessary oversight, auditing, and risk management of AI systems and their usage.
• Enablement: Providing the tools, resources, and support systems that facilitate responsible usage of AI systems.

The Emerging Technology Stack

Success in Generative AI demands a scalable architecture beyond just Large Language Models.

How Top Organizations are Utilizing Generative AI

To offer a practical perspective, here’s how various organizations are employing Writer:

• F50 Telecom Provider: Generates summaries, conversation starters, and next steps to aid customer service agents and executives in their interactions with customers.
• F50 Investment Bank: Produces personalized insights and conversation starters for senior bankers to engage with their clients and CEOs.
• F10 Healthcare Company: Personalizes instructions and information for patients based on their prescription, health considerations, and age.
• F100 Retail Bank: Generates responses to common questions and crafts personalized client communications for financial services salespeople.
• F100 Retailer: Analyzes influencer videos, extracting insights like pain points and expectations for market research and R&D.

Begin today with CX AI

Delaying an investment in AI could put you at risk of being out-innovated by your competitors. But you don’t have to start big. Our CX AI jumpstart helps you quickly identify opportunities for leveraging generative AI, demonstrate the value through technical proof of concept, and define the path forward to realizing your vision. Interested in a deeper dive?  Learn more about how our team can help you begin your AI journey today!

As the financial services industry continues to evolve, companies are looking for ways to stay ahead of the competition and increase their market share. One way to do this is by leveraging the power of generative AI. Generative AI is an advanced form of artificial intelligence that can create content from scratch, taking the burden off of manual labor and allowing companies to focus on their core business. As a leading digital transformation company, Perficient is committed to helping financial services clients integrate Generative AI into their business to augment workflows across every function. We understand the complexities of the industry and are here to make the process of integrating Generative AI as seamless as possible.

Through our partnership with Writer, an enterprise-grade generative AI platform, we are able to help our clients create personalized, compliant content faster than ever before. Our clients benefit from Writer’s API, which allows them to access their own fine-tuned model and customized applications. Generated output takes into account everything from brand voice and word and character length to fact verification, and includes up-to-date information. This is generative AI that’s ready for at-scale enterprise use cases — without needing to build an internal Machine Learning and Natural Language Processing team or application layer yourself.

Perficient also helps clients to create a consistent, unified voice across their product portfolio by leveraging Writer’s style guide and terms features. With the API and Figma plugin, they can empower everyone to use the language that differentiates them in a competitive industry. We also enable clients to use Writer’s snippets to follow strict compliance regulations and efficiently include disclosures in their sales and marketing.

Use Cases

Writer is the most customizable generative AI platform for banking, asset and wealth management, and insurance companies with implementations at many large financial service organizations including Charles Schwab, Vanguard, Intuit, and many more. Perficient can help deliver solutions to transform your organization.

Banking:

• Enhance cross-selling and customer acquisition efforts through connected banking by delivering personalized and targeted campaigns.
• Boost operational efficiency and rapid scalability by effortlessly generating new documents using existing data and content with the help of AI-powered document creation.

Wealth & asset management:

• Effortlessly extract key insights and key takeaways from longform written or audiovisual content using AI-generated executive and market summaries.
• Streamline the entire process, from ideation and outlining to drafting and revisions, to expedite the implementation of groundbreaking ideas into practice.

Insurance:

• Generate compelling content that enhances internal communication and fosters improved customer relationships through effective knowledge management practices.
• Enhance customer trust and minimize potential risks by establishing a centralized and reliable platform for regulatory disclosures, ensuring transparency.

An Alternative for Regulated Industries

At Perficient, we understand the importance of security when it comes to the financial services industry. Many leaders in highly regulated industries have concerns around Generative AI, as some platforms specifically recommend not sharing or inputting sensitive data. These platforms are not appropriate for financial service organizations, but there are solutions that will protect your data and customers. We ensure that the data of our clients is analyzed transiently, so what they edit or generate isn’t collected or used by Writer. Writer is compliant with the latest privacy and security standards, so our clients can confidently deliver secure customer experiences at scale.

Perficient is here to help financial services clients leverage the power of generative AI to increase their market share. From personalized communication to legal governance and compliance, AI can help you’re your business drive innovation with speed you can trust.

We’re committed to making the process of integrating Generative AI as seamless as possible. If you want to learn how generative AI can be leveraged for your company, consider our CX AI jumpstart.

Perficient is proud to sponsor the upcoming North American Financial Information Summit (NAFIS), taking place on May 16th, 2023. NAFIS is the largest North American data conference for banks and asset managers looking to the future of data in financial services. Registration is FREE if you work for a bank, asset manager, financial investor, fund manager or financial institution;  click here to receive your free ticket to NAFIS.  

A Can’t-Miss Experience 

This one-day event promises to be jam packed with informative presentations hosted by leaders from North America’s top  financial institutions.  

Perficient has been partnering with BNY Mellon to realize the promise of modern data management through a unified data lake, strong governance, and effective data mastering. Eric Hirschhorn, Chief Data Officer at BNY Mellon, and our very own Eric Walk, Director of Enterprise Data Strategy, will present on BNY Mellon’s progress on its data journey as well as industry trends. 

Visit Our Sponsor Booth! 

In addition to the presentations, attendees will also have the opportunity to network with peers, visit expos, and interact with sponsors at their booths. Make sure to stop by our booth to chat with a Perficient expert to learn more about who we are, what we do, and how we can work together to optimize your data journey!  

Click here to learn more about the event and schedule. Registration for your FREE NAFIS ticket is available through this link. 

As businesses strive to stay ahead in today’s competitive market, innovation and creativity have become crucial elements of success. However, the traditional process of content creation can be time-consuming and resource-intensive, leaving little room for experimentation and innovation. This is where Artificial Intelligence comes in. Generative AI is a groundbreaking technology that is transforming the way businesses think about content creation and experimentation. With its ability to produce original and creative outputs in a matter of seconds, generative AI tools can enable businesses to work at a faster pace, experiment with new ideas more easily, and ultimately stay ahead of the competition. Because the technology has advanced so quickly, with last year’s ChatGPT3 having 100 billion parameters and the newly released ChatGPT4 having 100 trillion parameters, for example, generative AI has gone from gimmicky to disruptive in a matter of years. But how can we take this technology and apply it in real, meaningful ways?

When we first entered this new wave of digital transformation, we experimented with fun applications of generative AI. While we see this technology being utilized on social media platforms and online, there must be a better use of this technology than generating an image of a gecko in a Renaissance painting style, right?

We’ve all heard of “digital first,” then “mobile first.” We are now truly in the era of “AI first.” Because the technology is so advanced and continuing to evolve each and every day, there is a huge opportunity for businesses in creative content generation. From visual content to audio, speech, text, and even code writing, generative AI is impacting all businesses in some way or another.

Visual Content

While the example of the Renaissance Gecko is one example of an image generated by artificial intelligence, businesses and creatives have a huge opportunity to implement this technology today. For example, these tools have the power to generate multiple versions of a new business logo in seconds. They can also help build content for social media, digital ads, and even web content. Because of the speed and efficiency, this technology is great for exploring concepts and ideas as a starting point that can later be refined.

Audio Content

Generative AI tools are powerful in creating audio content in various ways. The most common use case we’ve seen so far is Text-to-Speech (TTS). TTS technology uses machine learning algorithms to convert text into synthesized speech. TTS models can be trained on large amounts of audio data to produce high-quality and natural-sounding speech. There’s also huge potential in both speech synthesis and voice cloning. Speech synthesis refers to the process of generating speech from non-speech audio sources, such as text, images, or gestures. AI models can analyze the audio sources and generate speech that corresponds to the content. Voice cloning is a process of creating a digital replica of a person’s voice. AI models can analyze recordings of a person’s voice and generate a synthetic voice that sounds like the original speaker. There are hundreds of potential use cases for AI-generated audio content that is indistinguishable from human-generated content.

The Customer Journey

Where we see AI being significant for many businesses is in the planning process when it comes to the customer journey. For example, we can utilize AI to create different personas for one product. Let’s take car shopping: we can very quickly and easily generate a persona for a Gen Z car shopper and a persona for a mom with two teens. These personas will look very different, but because they are generated with such speed, it’s a great starting point. It’s important to note that these are not perfect for taking straight away, and that the customer journey will always require subject matter expert input. Eve Sangenito, Principal at Perficient, believes that “delivering effective AI-generated experiences requires careful considerations and should involve humans in the loop in order to review, revise, and finalize outputs.”

The real power, however, is when we combine multiple AI technologies and try to create something new. But how do we make it real and apply it to real-world scenarios? One use case to leverage Generative AI is in Journey Science. This is a proprietary discipline within Perficient to help organizations design customer-driven, frictionless experiences that are journey-focused. This practice combines researched-based insights with data-driven evidence to understand, predict and optimize the customer journey at every touchpoint. We see two specific applications within the Journey Science discipline that can help deliver individualized customer experiences.

Personalization

When we think of how AI can help personalize the customer journey, there are four main areas to consider: context, persona, behavior, and journey. Context considers the environmental factors and circumstances that surround an individual user story. Personas align a user’s needs and motivation with a pre-defined target. Behavior takes into consideration a user’s previous interactions to provide an evolving experience over time. And finally, journey drivers help determine where a particular customer fits within that journey. But how do we apply AI to these areas?

One example is by writing a product description targeting a specific persona, like “moms,” and comparing it to how it differs when requesting it to target “dads.” Based on features of the product, AI tools can help write product descriptions that will resonate with different audiences. For example, we had AI generate a product description for a lawn mower targeting moms. It highlighted features of the mower, including ease of use, how smooth it runs, and its reliability. Compared to the description targeting dads, we see different points being highlighted. This description calls out its power, how it’s built to last, and how durable it is. This can help you begin to ideate how you as a marketer may want to speak to your different audiences.

Experimentation

Because the technology is making tasks so quick and efficient, it becomes easier to experiment with web pages and learn what may resonate most with the customer. We can use AI technology to ask “what experimentation hypotheses can I create for this web product page?” to learn more. It can also generate ideas based on crawling a page and will call out things that are not relevant. Finally, it also helps answer questions like “what type of test can I perform on the page to increase conversions” and “what headlines can I test on this page for different audience?” This technology helps marketers think creatively and in new ways about their customer journey and how to best reach their target audience with efficiency.

Challenges and What’s to Come

However, this technology is not without its challenges. First, it is important to ensure accuracy in generated content as it may not always be of high quality and may contain errors or inconsistencies. Additionally, the quality of generated content is dependent on the quality and diversity of the data the AI model is trained on, which could result in bias or lack of originality. Credibility also comes into question as Google and other content evaluation tools are detecting AI-generated content, which may negatively impact SEO over time. Furthermore, outputs may require multiple attempts and still be difficult to understand and use, making it challenging to identify and correct errors or biases. Finally, ethical concerns must be considered as models can be used to generate harmful or offensive content, which can be damaging to brands or individuals. However, platforms such as OpenAI and Bing have prioritized ethical concerns, and we have seen significant improvements as each model evolves.

Generative AI is a groundbreaking technology that has the potential to transform the way we think about content creation and experimentation. With the ability to produce original and creative outputs in a matter of seconds, generative AI is allowing creatives and businesses to work at a faster pace and experiment with new ideas more easily than ever before. The potential applications of generative AI are vast and varied, and we are only beginning to scratch the surface of what this technology can do. As AI continues to evolve, it will be exciting to see how generative AI will transform the way we create and interact with content in the future.