If you’d told me twenty years ago that I’d be working in the technology industry, I would have laughed. My background? Art, history, and social services—not exactly the usual path to tech. I still sew and do needlework, and I miss the days when you had to check an answering machine or hunt down a pay phone. Honestly, I thrived without knowing what my second cousin, three times removed, had for breakfast this morning. Sometimes, I feel like the old guy on the corner yelling, “get off my lawn!”

But life has a way of surprising us. My career took a hard left turn and landed me in the world of technology. At first, I thought, “No problem. My skills—problem solving, analysis, and communication—are still useful.” I didn’t need to dive too deep into the tech pool; basic Excel and PowerPoint were enough. Fourteen years later, I’m proof that a non-technical person can survive (and even thrive) in a technology company.

Then came 2025. Our new CEO announced that we were going to be an AI-First company. We were not only encouraged, but expected to use AI in our day-to-day work. Cue the mini panic attack. My mind raced: What part of my job could I hand over to AI? How was I supposed to figure this out?

The lowest hanging fruit was my semi-annual reports. But I actually enjoy making those! Me and my trusty adding machine (yes, I still use it) making charts and graphs, discovering trends, and recapping the year—it’s something I look forward to. I didn’t want to give that away to my computer.

But change was coming, whether I liked it or not. So, I took a deep breath and got on board. I completed every training offered and sat down with a coworker who was genuinely excited about AI. Together, we made a plan and found ways to integrate AI into my workflow. Anytime someone said, “You can use Copilot for that,” I’d ask how. Gradually, my panic eased and I started to see the possibilities.

Now, I use Copilot to summarize long technical documents in plain language, generate images for presentations, and organize meeting notes. I’m still not ready to give up my trusty adding machine or hand over my reports, but I’m finding other ways to use these tools to make my life easier.

Most people see AI as something that gives them more time in their day. I used to think it would take away the parts of my job I enjoyed. Turns out, I was mistaken. If you’re like me—afraid of adopting new technology and unsure how it can help—take a deep breath and start small. Try it out and see if it really does save you time. And if you haven’t asked Copilot to rewrite an email as if it were from a pirate yet, you’re missing out! Not every use case works for everyone, but everyone can find a use case.

So here’s my advice:
You don’t have to be an expert to benefit from AI. Start with one small task, ask questions, and let curiosity lead the way. You might be surprised at how much easier your work becomes—and you might even have a little fun along the way.

PS… I was able to use this post as a learning opportunity.  I asked Copilot to review my article and make suggestions – most of which made the final draft.  Another small step.

We’re thrilled to announce that Perficient is a proud sponsor of Sitecore Symposium 2025, the premier event for digital experience leaders, marketers, and technologists. This year’s event takes place November 3-5 at the Walt Disney World Dolphin Resort in Orlando, FL. It promises to be a dynamic gathering of thought leaders and innovators, and Perficient is bringing a strong presence with four featured sessions that showcase our expertise in experience design, strategy, digital marketing, and analytics to create end-to-end solutions that deliver exceptional results.

As you’re mapping out your agenda, make sure to schedule some time to stop by our booth to meet our team of Sitecore MVPs, strategists, and technologists and catch a live demo of Sitecore’s products and our AI acceleration tools. Curious about the Sitecore and Gradial partnership and how you can benefit from agentic marketing? Our team would be thrilled to discuss our thoughts on what this can mean for your organization.

What We’re Talking About and When

We’re excited to take the stage with both Encompass Health and Evergy this year! If you’re looking to harness the power of customer data, design more inclusive experiences, or lead through change, our sessions offer something for everyone.

Back by popular demand, the first ever Women in Digital event that Perficient proudly co-sponsored with Sitecore last year is quickly becoming a “must attend” event on the conference schedule. This year’s theme is Leading Through Change and once again, Perficient’s own Megan Jensen will moderate a panel of inspiring women to dive into this topic.

Women and allies alike are welcome to experience this unique opportunity to hear from remarkable women, network with peers, and enjoy breakfast. Register early to reserve your spot. We look forward to seeing you there!

Women in Digital: Leading Through Change

In a landscape reshaped by AI, rerouted customer journeys, and the collapse of traditional content-to-commerce paths, leadership demands agility, empathy, and vision. This intimate breakfast panel brings together trailblazing women from across the digital ecosystem to explore how they’re navigating transformation—scaling trust, driving innovation, and fostering inclusion in real time. Join us for a candid conversation on what it means to lead now, what’s next, and how we build the future together.

What’s Your Data Doing for You? Learn How to Harness the Power of Your Data With Sitecore CDP

Your company possesses valuable customer data, but are you using it strategically? Join Perficient’s Eric Sanner, solutions architect and 2x Sitecore MVP, along with a marketing leader from Midwest utility company Evergy, to discuss how the company utilizes Sitecore CDP to combine data from multiple sources into one flexible, powerful, easy-to-use platform. Learn how to breathe new life into marketing strategies by creating sophisticated segmentation that targets high-value customers. See how CDP and Personalize can give marketers autonomy while reducing costs.

Designing Inclusive Experiences for Everyone: Build a Better Journey Map on Sitecore

Explore common disability tropes and stereotypes, the intersection of accessibility and representation, and the importance of showing diversity in advertising, marketing, and media. In this session, you’ll learn about UX challenges for disabled users, brainstorm improvements, and collaboratively design a user journey that addresses the needs of a disabled persona. These insights will help shape your understanding of the Sitecore products and platforms that enable inclusive experiences.

Unveiling Encompass Health’s Digital Transformation: A Panel on Lessons Learned With a Bit of SaaS

Join Perficient’s Stephen Tynes, national Sitecore sales advisor, and Mark Ursino, Sitecore principal, as they team up with marketing leaders from Encompass Health to share the organization’s digital transformation journey. Learn how the organization approached patient and caretaker research, fostered internal collaboration, and managed change with IT to drive success. We’ll address the challenges encountered, the outcomes achieved, and touch upon key topics such as the Sitecore roadmap and strategy to move from on-prem XP to SaaS XM Cloud.

A Sitecore Platinum Partner, Ready to Support You

Perficient is a global AI-first consultancy helping clients move faster, engage smarter, and connect deeper with customers. We’re a Sitecore 2024 Practice Excellence Award – Global winner with specialties in XM Cloud, CDP/Personalize, OrderCloud, Content Hub, and XP.

We’ll be on-site throughout the event to connect, collaborate, and share how we’re helping organizations unlock the full potential of Sitecore. Whether you’re exploring a move to XM Cloud, looking to optimize your personalization strategy, or simply want to chat about the future of digital experience, we’re here to help you make the most of your Symposium experience.

Acquia is known for its open-source roots and marketer-friendly tools, and its approach to AI reflects that ethos. As digital experience platforms evolve, Acquia is embedding agentic and Generative AI to make experience creation more accessible, intuitive, and scalable, especially for teams without deep technical resources. 

Forrester’s report, The Impact of AI on Digital Experience Platforms, discusses how vendors like Acquia are using AI to simplify workflows, automate content generation, and empower practitioners across roles — and Acquia’s recent innovations reflect its commitment to democratizing digital experience delivery. 

Supporting Marketers Behind the Scenes With Agentic AI

Launched earlier this year, Acquia Source allows marketers to build web pages using AI prompts that generate code behind the scenes and eliminate the need for developer intervention. These agentic capabilities are designed to reduce friction and accelerate time to market for digital experiences. 

Perficient DXP Practice Director Josh Hover and his team have been helping clients take advantage of these capabilities to streamline experience creation.  

Josh said, “Acquia’s agentic AI tools are helping marketers take control of experience creation. We’re working with clients to integrate these capabilities into their workflows so they can move faster without sacrificing quality.” 

Simplifying Experience Creation with GenAI

Acquia has been embedding GenAI into its platform for years. For example, it partnered with Clarifai to provide image auto-tagging. Today, however, GenAI is powering more advanced use cases. From generating page layouts to summarizing customer interactions, teams can deliver relevant experiences with less manual effort. 

Reflecting on these innovations, Josh notes how GenAI is helping teams scale without adding complexity.  

“Acquia’s GenAI features are especially valuable for teams with limited resources. We’re helping clients use these tools to scale content and streamline operations without being complicated,” he said.  

Perficient Named 2025 Gold Globe® Winner for Best Artificial Intelligence Service Provider | Learn More 

Enabling Responsible AI Adoption Across Teams

Successful AI adoption requires strong data foundations, human oversight, and change management. Acquia’s focus on accessibility makes these considerations even more critical. That’s why we partner with clients to ensure AI tools are deployed responsibly and aligned with business goals. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Acquia. Whether it’s orchestrating personalized journeys or deploying intelligent agents, we’re helping brands embrace AI responsibly and effectively. 

If you’re exploring how to bring AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Acquia expertise here.  

Contact us to learn more. 

As customer expectations continue to rise, financial services organizations are under increasing pressure to deliver personalized, seamless, and secure digital experiences. Adobe’s latest report, The Total Economic Impact of Adobe’s Content Supply Chain Solution, reveals how Generative AI and connected data are reshaping the industry and why now is the time for financial institutions to evolve.

A Wake-Up Call for Financial Services

Consumers today expect more than just secure transactions. They want personalized recommendations, consistent omnichannel experiences, and transparency in how their data and AI-generated content are used. Yet, Adobe’s research shows a significant gap between these expectations and what financial services brands currently deliver:

• 90% of consumers rate data privacy as critical, but only 58% feel their data is handled securely
• 79% expect consistent experiences across channels, but just 47% say brands deliver
• Only 33% feel brands anticipate their needs with relevant offers, despite 70% expecting it

This disconnect presents a clear opportunity for financial institutions to differentiate themselves by investing in AI-powered personalization and content delivery.

GenAI Moves From Concept to Competitive Advantage

Generative AI is no longer a futuristic concept; it is now a reality. It’s a strategic imperative. In 2025, 56% of financial services organizations are prioritizing GenAI to improve client interactions and employee productivity. Wealth and asset management firms lead the charge with 60% focusing on AI-driven client engagement compared to 52% in retail banking.

Use cases are expanding rapidly:

• Chatbots are the most mature application, with 49% of organizations already using them
• Journey optimization and data analysis are gaining traction, with over 40% of firms piloting or deploying solutions
• AI is also being used to automate workflows, generate creative content, and personalize customer experiences across channels

Efficiency, Engagement, and Growth

Executives are already seeing tangible benefits from AI adoption:

• 51% report major gains in content production speed
• 50% see improved team productivity
• 47% note freed-up resources for strategic initiatives

These improvements are driving better customer engagement and laying the foundation for scalable, personalized marketing.

Overcoming Compliance, Data Silos, and Culture

Despite the momentum, scaling AI in financial services isn’t without challenges. Governance, compliance, and privacy concerns top the list, especially in retail banking, where 59% of executives cite compliance as the biggest hurdle. Siloed data is another major issue, particularly in wealth and asset management, where 51% struggle to unify customer insights.

To move forward, organizations must:

• Establish cross-functional AI governance committees
• Invest in real-time data platforms
• Prioritize ethical AI practices to protect brand reputation

The Road Ahead

The Adobe report paints a clear picture: financial services organizations must embrace AI and digital transformation to stay competitive. Key trends shaping the future include:

• Hyper-Personalization | Real-time, one-to-one interactions are the goal, but only 33% of firms can update offers based on browsing history.
• Omnichannel Consistency | Practitioners feel pressure to deliver more content across more channels, with 43% citing increased volume demands.
• Sustainable Innovation | Wealth managers are leading the way in sustainable investing, responding to growing consumer demand.

To succeed, financial institutions must take a methodical, compliant approach to AI adoption, balancing innovation with trust. The winners will be those who connect data, content, and customer insights to deliver meaningful, personalized experiences at scale.

Ready to Transform Your Digital Experience Strategy?

Navigating the complexities of AI adoption, data governance, and digital transformation requires more than just technology. It demands deep industry expertise and a strategic partner who understands the nuances of financial services.

Our experts bring together Adobe solutions, generative AI innovation, and financial services experience to help you:

• Deliver personalized, compliant, and scalable digital experiences
• Break down data silos and activate real-time insights
• Accelerate content creation and journey optimization with AI
• Build trust through secure, transparent, and consistent customer interactions

Whether you’re modernizing for next-gen customers, launching new digital offerings, or scaling AI across your organization, we’re here to help you move forward with confidence.

Let’s connect and explore how we can elevate your customer experience together.

Optimizely has always been synonymous with experimentation. Its platform empowers organizations to test, learn, and optimize digital experiences with precision. Now, with the integration of agentic and generative AI, Optimizely is taking that mission further — helping teams not only run smarter experiments but also act on insights faster and more confidently. 

Forrester’s report, The Impact of AI on Digital Experience Platforms, discusses how vendors like Optimizely are embedding AI to support content creation, campaign testing, and practitioner enablement. Optimizely’s approach stands out for its focus on agility and continuous improvement. 

Agentic AI Turns Data Into Decisions

Optimizely’s Opal provides a unified view of customer interactions, enabling marketers to make informed decisions based on real-time data. Agentic AI capabilities are layered into this experience, offering recommendations, automating workflows, and guiding practitioners through complex optimization paths. 

Perficient Optimizely Director David Lewis explains how Perficient is helping clients unlock the full potential of these tools.  

Lewis said, “We’re seeing Optimizely’s AI capabilities accelerate how teams work—whether it’s Opal generating brand-consistent content in CMP, summarizing experiment results in Web Experimentation, or surfacing personalization ideas directly in Feature Experimentation. The real advantage is that these tools are connected to the workflows practitioners already use every day, so optimization happens naturally and at scale.” 

Accelerating Content and Campaign Innovation With GenAI

Optimizely’s GenAI features are designed to support rapid iteration. From generating brand-consistent content to summarizing customer behavior and simulating campaign outcomes, GenAI is helping teams move faster without compromising quality. 

Lewis shares how Perficient is guiding clients through this transformation. 

“We’re seeing GenAI help Optimizely users move faster, whether it’s writing audience-specific content or simulating campaign outcomes. The key is integrating these tools into workflows that already drive business value,” he said.  

Perficient Named 2025 Gold Globee® Winner for Best Artificial Intelligence Service Provider | Learn More 

Building a Smarter, Safer AI Strategy

Successful AI adoption requires strong data foundations, human oversight, and change management. That’s why we work with clients to ensure these elements are in place, especially when integrating AI into experimentation and optimization workflows. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Optimizely. Whether it’s orchestrating personalized journeys or deploying intelligent agents, we’re helping brands embrace AI responsibly and effectively. 

If you’re exploring how to bring Optimizely’s AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Optimizely expertise here.  

Contact us to learn more.

Over the past few months, I have shared a couple of blogs exploring embedded personalization in Sitecore XM Cloud:

• Personalization in Sitecore XM Cloud: What’s New, What’s Different, and What It’s Built On! – where I introduced the out-of-the-box personalization capabilities in XM Cloud.
• Getting Started with Personalization in Sitecore XM Cloud: Enable, Extend, and Execute  – where I walked through how to set up personalization and begin using it effectively.

While XM Cloud embedded personalization (found within Pages) offers an excellent, out-of-the-box solution for common personalization needs, it has a key limitation: it restricts you to a predefined set of marketer-friendly conditions. This streamlined, page-variant-based approach is quick to implement for scenarios like localizing content by geography or targeting new vs. returning visitors, making it a great starting point for content authors.

The Need for a Deeper Personalization Engine

But here’s the limitation: XM Cloud is built for speed, scalability, and a smooth content authoring experience. It doesn’t let you create custom conditions inside Pages. In legacy Sitecore XP, developers could extend the rule engine with custom C# code. In XM Cloud, the design is different. For any personalization logic beyond basic, marketer-friendly, out-of-the-box rules (like device type or referrer), Sitecore directs you to its dedicated, cloud-native platform – Sitecore Personalize.

This is where the world of digital experience often demands logic that goes beyond these basic audience segments. When you need to personalize based on proprietary business rules, custom data streams, or complex, multi-touchpoint journeys, the embedded tools won’t suffice.

This is where Sitecore Personalize becomes essential. Personalize is a standalone, cloud-native personalization and decisioning engine built to handle advanced scenarios.

Sitecore Personalize: The Technical Extension

Personalize acts as the key to unlocking limitless personalization power within your XM Cloud solution.

• Custom Conditions: The most critical technical feature is the ability to define developer-written custom conditions. These conditions are authored in JavaScript within Personalize, built once by a developer, and then exposed to marketers for endless reuse within the XM Cloud Pages audience builder. This allows you to create highly tailored audience rules based on any data you can pipe into the platform.
• Advanced Decisioning and Experimentation: Personalize is API-first, supporting complex decision models, A/B testing, and multi-variant experiments that can go far beyond simple page variants. It includes dedicated dashboards and robust analytics for measuring the performance of these sophisticated experiences.
• Cross-Channel Orchestration: Personalize is designed to be truly cross-channel. Its capabilities extend beyond just the website, enabling you to orchestrate consistent, personalized experiences across email, mobile apps, and other API-driven touchpoints—leveraging a unified profile of the customer.

In short, Personalize extends XM Cloud’s personalization boundaries, making it possible to design highly tailored user journeys without being locked into out-of-the-box conditions.

This blog is the next step in the series: a developer-friendly deep dive into how Personalize works with XM Cloud.

XM Cloud and Personalize Integration

The seamless delivery of personalized content relies on a robust technical connection between your XM Cloud content management environment and the Sitecore Personalize decision engine. This part often feels like “black box magic,” so let’s clarify the two key phases: initial provisioning and run-time execution.

Provisioning & Tenant Setup

When an organization purchases a Sitecore Personalize license, the initial setup is managed by Sitecore Professional Services or your dedicated implementation partner. This process ensures the two separate cloud products are securely linked.

The typical process involves:

• Tenant Mapping: Establishing a clear connection between your environments (e.g., XM Cloud Dev/Test connecting to a Non-Production Personalize tenant, and XM Cloud Production connecting to a Production Personalize tenant). This separation is crucial for ensuring you don’t mix test audiences and conditions with real production traffic.
• Portal Access: You’ll receive invites to both the Sitecore Cloud Portal and the Personalize portal.
• Site Identifier Configuration: A Site Identifier must be created and mapped within XM Cloud. This is a critical technical step that tells Personalize exactly which rendering host (your website) it’s communicating with.

Important: Don’t be surprised if you don’t see your new custom condition in XM Cloud Pages right away—always first check that the site identifier is configured correctly and that the tenant setup is complete. Once this is wired, your XM Cloud Pages environment can successfully surface custom conditions and experiences created in Personalize.

Runtime Architecture: How the Two Talk at Request Time

Once environments are provisioned, your XM Cloud rendering host (typically a Next.js application) needs to fetch the correct personalization decision for every page request.

The Sitecore Cloud SDK is the exclusive and recommended method for integrating personalization and A/B/n testing within JSS SDK Next.js applications hosted on XM Cloud. This is designed to leverage Next.js Middleware and server-side rendering (SSR) for optimal performance. But let us take a look at both the SDKs that can be used to integrate with Personalize:

Personalization Data Flow Summary (SSR/Edge)

The personalization flow for a dynamic (SSR/Edge) page is a server-side handshake orchestrated by the Next.js Middleware and the Cloud SDK:

• Initial Check (JSS/Next.js $\to$ Experience Edge): The Next.js Middleware first queries Experience Edge to verify if any personalization variants exist for the page.
• Decisioning Call (JSS/Next.js $\to$ Personalize): If variants are found, the Middleware uses the Cloud SDK to send the visitor’s context to Sitecore Personalize.
• Variant ID Returned (Personalize $\to$ JSS/Next.js): Personalize evaluates all rules and returns the winning Variant ID (or the default ID) based on the evaluated rules.
• Content Fetch (JSS/Next.js $\to$ Experience Edge): The rendering host then makes a second request to Experience Edge, fetching the specific content layout matching the winning Variant ID.
• Final Delivery: The fully personalized HTML is rendered on the server and delivered to the visitor, ensuring a flicker-free experience.

Static Site Generation (SSG) Personalization Flow

The personalization process for pages built with SSG differs slightly from SSR to gain performance benefits by leveraging pre-generated HTML:

• Initial Request: When a visitor requests an SSG page, the Next.js application receives the standard HTTP request details (cookies, headers).
• Pre-Render Check: The Personalize middleware first checks its cache to see if static HTML variants have already been pre-rendered for this page.If a static variant is found, the middleware skips the initial API query to Experience Edge, speeding up the process. If no static variants are found, the process falls back to the standard SSR flow to dynamically fetch personalized variants from the CMS/Edge.
• Audience Decision: Assuming variants exist, the middleware sends a request to the Personalize (via the Cloud SDK) to identify which audience the current visitor belongs to.
• Delivery:
  • If the visitor matches an audience and that variant was already pre-generated, the middleware simply returns the cached static HTML for the personalized variant immediately.
  • If the visitor matches an audience but the static variant has not yet been built, the Next.js application generates the page variant HTML on the fly and then caches that output to serve as a static asset for all future visitors belonging to that same audience.
  • If the visitor does not match any defined audience, the generic default static HTML page is returned.

This method allows high-traffic personalized pages to benefit from the speed of static hosting after the first request generates the variant HTML.

Wrapping Up

Bringing Sitecore XM Cloud and Sitecore Personalize together creates a powerful framework for delivering experiences that adapt in real time. While XM Cloud manages structured content and headless delivery, Personalize adds a decisioning layer that evaluates context, behaviors, and data signals to tailor each interaction.

This integration not only extends the personalization capabilities of XM Cloud beyond static rules but also enables continuous testing, optimization, and experimentation. For teams building modern digital experiences, this approach provides the agility to serve relevant, data-driven content at scale – while maintaining the flexibility of a cloud-native, headless architecture.

In my next blog, I’ll walk through creating custom conditions in Sitecore Personalize, so you can define personalization logic that truly aligns with the unique business needs.

Sitecore has long positioned itself as a leader in composable digital experience platforms, offering flexibility and scalability for organizations looking to tailor their tech stacks. As AI becomes a central force in experience delivery, Sitecore is embedding agentic and Generative AI capabilities to help brands personalize at scale, streamline operations, and empower practitioners. 

Forrester’s report, The Impact of AI on Digital Experience Platforms, discusses how vendors like Sitecore are evolving their platforms to support intelligent orchestration and content creation. Sitecore’s modular architecture makes it uniquely suited to adopt these innovations. 

Empowering Practitioners With Agentic AI

Sitecore’s copilot launched in late 2024 and is designed to help marketers build hyper-personalized campaigns with less manual effort. These intelligent agents assist with segmentation, content recommendations, and campaign optimization all while integrating seamlessly into Sitecore’s composable stack. 

Perficient Sitecore Consulting Principal Mark Ursino has seen growing interest in Sitecore’s agentic AI capabilities, especially among clients looking to unify customer data and reduce friction in campaign execution. 

Ursino said, ” Sitecore’s AI orchestration capability, Stream, launched in late 2024 and is helping marketers move faster and smarter. We’re working with clients to integrate these tools into their workflows so they can focus on strategy while AI handles the complexity.” 

GenAI in a Composable World

Sitecore’s GenAI features are designed to complement its modular approach. Whether generating brand-consistent content, summarizing customer interactions, or supporting A/B testing, GenAI is helping teams deliver more relevant experiences without overhauling their existing infrastructure. 

“Sitecore’s composable architecture makes it easier to plug in GenAI capabilities where they’ll have the most impact. We’re helping clients identify those opportunities and align them with measurable goals,” said Ursino.  

Perficient Named 2025 Gold Globee® Winner for Best Artificial Intelligence Service Provider | Learn More 

Building a Responsible AI Foundation

Successful AI adoption requires more than just new features. Organizations must invest in strong data foundations, human oversight, and change management. That’s why we partner with clients to ensure these pillars are in place, especially when integrating AI into modular environments like Sitecore. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Sitecore. Whether it’s orchestrating personalized journeys or deploying intelligent agents, we’re helping brands embrace AI responsibly and effectively. 

If you’re exploring how to bring AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Sitecore expertise here.  

Contact us to learn more. 

The AI Revolution is in Drupal CMS 

The way we create, optimize, and deliver content has fundamentally changed. Artificial Intelligence is no longer a futuristic concept; it’s a practical, indispensable tool for content teams. For years, Drupal has been the gold standard for structured, enterprise-level content management. Now, with the rapid maturation of the community’s Artificial Intelligence Initiative, Drupal is emerging as the premier platform for an Intelligent CMS. 

This post is for every content editor, site builder, and digital marketer who spends too much time on repetitive tasks like writing alt text, crafting meta descriptions, or translating copy. We’re moving the AI power from external tools directly into your Drupal admin screen. 

We will explore five essential Drupal modules that leverage AI to supercharge your content workflow, making your team faster, your content better, and your website more effective. This is about making Drupal work smarter, not just harder. 

The collective effort to bring this intelligence to Drupal is being driven by the community, and you can see the foundational work, including the overview of many related projects, right here at the Drupal Artificial Intelligence Initiative. 

1. AI CKEditor Integration: The Content Co-Pilot

This functionality is typically provided by a suite of modules, with the core framework being the AI (Artificial Intelligence) module and its submodules like AI CKEditor. It integrates large language models (LLMs) like those from OpenAI or Anthropic directly into your content editor. 

Role in the CMS 

This module places an AI assistant directly inside the CKEditor 5 toolbar, the primary rich-text editor in Drupal. It turns the editor from a passive text field into an active, helpful partner. It knows the context of your page and is ready to assist without ever requiring you to leave the edit screen. 

How It’s Useful 

• For Content Editors: It eliminates the dreaded “blank page syndrome.” Highlight a bulleted list and ask the AI to “turn this into a formal paragraph” or “expand this summary into a 500-word article.” You can instantly check spelling and grammar, adjust the tone of voice (e.g., from professional to friendly), and summarize long blocks of text for teasers or email excerpts. It means spending less time writing the first draft and more time editing and refining the final, human-approved version. 

• For Site Builders: It reduces the need for editors to jump between Drupal and external AI tools, streamlining the entire content creation workflow and keeping your team focused within the secure environment of the CMS. 

2. AI Image Alt Text: The SEO Automator

AI Image Alt Text is a specialized module that performs one critical task exceptionally well: using computer vision to describe images for accessibility and SEO. 

Role in the CMS 

This module hooks into the Drupal Media Library workflow. The moment an editor uploads a new image, the module sends that image to a Vision AI service (like Google Vision or an equivalent LLM) for analysis. The AI identifies objects, actions, and scenes, and then generates a descriptive text which is automatically populated into the image’s Alternative Text (Alt Text) field. 

How It’s Useful 

• For Accessibility: Alt text is crucial for WCAG compliance. Screen readers use this text to describe images to visually impaired users. This module ensures that every image, regardless of how busy the editor is, has a meaningful description, making your site more inclusive right from the start. 

• For SEO & Editors: Alt text is a ranking signal for search engines. It also saves the editor the most tedious part of their job. Instead of manually typing a description like “Woman sitting at a desk typing on a laptop with a cup of coffee,” the AI provides a high-quality, descriptive draft instantly, which the editor can quickly approve or slightly refine. It’s a huge time-saver and compliance booster. 

3. AI Translation: The Multilingual Enabler

This feature is often a submodule within the main AI (Artificial Intelligence) framework, sometimes leveraging a dedicated integration like the AI Translate submodule, or integrating with the Translation Management Tool (TMGMT). 

Role in the CMS 

Drupal is one of the world’s most powerful platforms for building multilingual websites. This module builds upon that strength by injecting AI as a Translation Provider. Instead of waiting for a human translator for the first pass, this module allows content to be translated into dozens of languages with the click of a button. 

How It’s Useful 

• For Global Content Teams: Imagine launching a product page simultaneously across five markets. This tool performs the initial, high-quality, machine-generated translation and saves it as a draft in the corresponding language node. The local editor then only needs to perform post-editing (reviewing and culturally adapting the text), which is significantly faster and cheaper than translating from scratch. 

• For Site Owners: It drastically cuts the time-to-market for multilingual content and ensures translation consistency across technical terms. It leverages the AI’s power for speed while retaining the essential human oversight for cultural accuracy. 

4. AI Automators: The Smart Curator

AI Automators (a powerful submodule of the main AI project) allows you to set up rules that automatically populate or modify fields based on content entered in other fields. 

Role in the CMS 

This is where the magic of “smart” content happens. An Automator is a background worker that monitors when a piece of content is saved. You can configure it to perform chained actions using an LLM. For instance, when an editor publishes a new blog post: 

1. Read the content of the Body field. 
2. Use a prompt to generate five relevant keywords/topics. 
3. Automatically populate the Taxonomy/Tags field with those terms. 
4. Use another prompt to generate a concise post for X (formerly Twitter). 
5. Populate a new Social Media Post field with that text. 

How It’s Useful 

• For Content Strategists: It enforces content standards and completeness. Every piece of content is automatically tagged and optimized, reducing the chance of human error and improving content discoverability through precise categorization. It ensures your SEO and content strategy is executed flawlessly on every save. 

• For Site Builders: It brings the power of Event-Condition-Action (ECA) workflows into the AI space. It’s a no-code way to build complex, intelligent workflows that ensure data integrity and maximize the usefulness of content metadata. 

5. AI Agents: The Operational Assistant

AI Agents, typically used in conjunction with the main AI framework, is a powerful new tool that uses natural language to execute administrative and site-building tasks. 

Role in the CMS

An AI Agent is like a virtual assistant for your Drupal back-end. Instead of navigating through multiple complex configuration forms to, say, create a new field on a content type, you simply tell the Agent what you want it to do in plain English. The Agent interprets your request, translates it into the necessary Drupal API calls, and executes the changes. The module comes with various built-in agents (like a Field Type Agent or a Content Type Agent). 

How It’s Useful 

• For Site Builders and Non-Technical Admins: This is a revolutionary step toward conversational configuration. You can issue a command like: “Please create a new Content Type called ‘Product Review’ and add a new text field named ‘Reviewer Name’.” The agent handles the creation process instantly. This dramatically reduces the learning curve and time needed for common site-building tasks. 

• For Automation: Agents can be chained together or triggered by other systems to perform complex, multi-step actions on the CMS structure itself. Need to update the taxonomy on 50 terms? A dedicated agent can handle the large-scale configuration change based on a high-level instruction, making system maintenance far more efficient. It turns administrative management into a conversation. 

Conclusion:

The integration of AI into Drupal is one of the most exciting developments in the platform’s history. It is a powerful affirmation of Drupal’s strength as a structured content hub. These modules—the AI CKEditor, AI Image Alt Text, AI Translation, AI Automators, and now the transformative AI Agents—are not here to replace your team. They are here to empower them. 

By automating the mundane, repetitive, and technical aspects of content management and even site configuration, these tools free up your content creators and site builders to focus on what humans do best: strategy, creativity, and high-level decision-making. The future of content management in Drupal is intelligent, efficient, and, most importantly, human-powered. It’s time to equip your team with these new essentials and watch your digital experiences flourish. 

Here’s Why Perficient’s Elite Partner Status Will Make a Difference 

Databricks recently announced its acquisition of Tecton, a leading real-time feature store, to expand its AI agent capabilities. The move, covered by outlets including Reuters, InfoWorld, and AiTech365, enhances Databricks’ real-time data processing within Agent Bricks, enabling ultra-fast, contextual decision-making across use cases such as fraud detection, personalization, and risk scoring. 

What Does the Tecton Acquisition Mean for Databricks? 

The acquisition is significant because it closes one of the largest gaps in moving AI from experimentation to production at scale. Building on Tecton’s long-standing partnership and investor ties with Databricks—as well as shared clients like Coinbase—the deal strengthens Databricks’ market position and accelerates its ambition to lead enterprise AI infrastructure. 

Why it Matters: 

Real-Time AI Capabilities 

• Tecton’s feature platform enables sub-10 ms feature serving, allowing AI agents and applications to respond instantly with fresh data (fraud detection, chatbots, personalized recommendations). 

• By bringing this into Databricks, enterprises can now handle data prep, model training, and real-time inference all on one unified platform. 

Seamless Workflows from Raw Data to Production AI 

• Traditionally, teams stitched together multiple tools for data engineering, feature engineering, and deployment—causing delays and friction. 

• With Tecton integrated, Databricks now offers a streamlined path from raw data → features → models → production, reducing complexity and accelerating time-to-value. 

Enterprise-Grade Scale and Governance 

• Companies often struggle to reuse features across teams or maintain consistency between training and production. Tecton standardizes this process, improving accuracy and governance.

• Now, enterprises get that consistency inside the Databricks intelligence ecosystem—without juggling extra platforms. 

Ecosystem Strength 

• The acquisition expands Databricks’ capabilities into feature store and real-time AI territory. 

• For enterprises already on Databricks, it eliminates the need to adopt yet another specialized tool. 

Perficient: An Elite Partner in Real-Time AI Adoption 

As of March 17, 2025, Perficient achieved Databricks Elite Partner status, recognizing our deep expertise across data engineering, AI/ML, analytics, and governance. With more than 160 Databricks-certified consultants, we deliver end-to-end, mission-ready solutions—from lakehouse design to MLOps/LLMOps—across Azure, AWS, and GCP. 

Perficient was on the ground at the Databricks Data + AI World Tour 2025 in Dallas on September 4th, immediately following the Tecton announcement. 

“The acquisition of Tecton marks a turning point in how enterprises operationalize AI. By embedding real-time feature serving directly into the Databricks Intelligence Platform, organizations can build AI systems that not only learn but also react instantly to business-critical events,” said Nick Passero, director of Databricks at Perficient.

“As a Databricks Elite Partner, Perficient is uniquely positioned to help clients harness this capability—guiding them through integration, optimizing their architectures, and accelerating their path from experimentation to enterprise-scale AI.”    

Now with Tecton’s real-time feature services in the fold, Perficient is ideally positioned to help clients integrate, optimize, and scale—turning data intensity into AI agility. 

Three Ways Perficient Can Help Clients Harness Tecton-Powered AI 

1. Integration Best Practices: Perficient guides clients on embedding Tecton-powered real-time feature serving into their existing Databricks environments—ensuring workflows remain seamless, performant, and cost-effective. 

1. Accelerated Innovation with Confidence: With Tecton’s sub-10 ms latency, sub-100 ms freshness, and 99.99% uptime guarantees, Perficient helps clients deploy responsive agentic systems backed by enterprise-grade reliability. 

1. Comprehensive, Future-Ready AI Architectures: From strategy and design to deployment and governance, Perficient architects full-stack AI systems—including real-time feature stores, MLOps pipelines, AI agents, and dashboards—for use cases spanning personalization to risk mitigation. 

Build with Databricks + Perficient 

Databricks’ acquisition of Tecton is a milestone in the evolution of AI infrastructure. It empowers enterprises to build AI agents that think, react, and adapt in real time. Perficient, with our Elite Partner status, deep technical expertise, and strategic advisory capabilities, is ready to help organizations harness this shift and translate it into measurable business outcomes. 

Want to get started? Reach out to our Databricks experts to explore how real-time AI agents powered by Tecton can redefine your business. 

In modern cloud infrastructure development, writing Terraform code manually can be time-consuming and error-prone—especially for teams that frequently deploy modular and scalable environments. There’s a growing need for tools that:

• Allow natural language input to describe infrastructure requirements.
• Automatically generate clean, modular Terraform code.
• Integrate with cloud authentication mechanisms.
• Save and organize code into execution-ready files.

This model bridges the gap between human-readable Infrastructure descriptions and machine-executable Terraform scripts, making infrastructure-as-code more accessible and efficient. To build this model, we utilize CodeGemma, a lightweight AI model optimized for coding tasks, which runs locally via Ollama.

In this blog, we explore how to build a Terraform code generator web app using:

• Flask for the web interface
• Ollama’s CodeGemma model for AI-powered code generation
• Azure CLI authentication using service principal credentials
• Modular Terraform file creation based on user queries

This tool empowers developers to describe infrastructure needs in natural language and receive clean, modular Terraform code ready for deployment.

Technologies Used

CodeGemma

CodeGemma is a family of lightweight, open-source models optimized for coding tasks. It supports code generation from natural language.

Running CodeGemma locally via Ollama means:

• No cloud dependency: You don’t need to send data to external APIs.
• Faster response times: Ideal for iterative development.
• Privacy and control: Your infrastructure queries and generated code stay on your machine.
• Offline capability: Ideal for use in restricted or secure environments.
• Zero cost: Since the model runs locally, there’s no usage fee or subscription required—unlike cloud-based AI services.

Flask

We chose Flask as the web framework for this project because of its:

• Simplicity and flexibility: Flask is a lightweight and easy-to-set-up framework, making it ideal for quick prototyping.

Initial Setup

• Install Python.

winget install Python.Python.3

• Install Visual Studio.
• Install Download Ollama on Windows.
• Pull and run the codegemma:7b.

ollama pull codegemma:7b
ollama run codegemma:7b

• Install the Ollama Python library to use Gemma 3 in your Python projects.

pip install ollama

Folder Structure

Code

from flask import Flask, jsonify, request, render_template_string
from ollama import generate
import subprocess
import re
import os

app = Flask(__name__)
# Azure credentials
CLIENT_ID = "Enter your credentials here."
CLIENT_SECRET = "Enter your credentials here."
TENANT_ID = "Enter your credentials here."

auth_status = {"status": "not_authenticated", "details": ""}
input_fields_html = ""
def authenticate_with_azure():
    try:
        result = subprocess.run(
            ["cmd.exe", "/c", "C:\\Program Files\\Microsoft SDKs\\Azure\\CLI2\\wbin\\az.cmd",
             "login", "--service-principal", "-u", CLIENT_ID, "-p", CLIENT_SECRET, "--tenant", TENANT_ID],
            capture_output=True, text=True, check=True
        )
        auth_status["status"] = "success"
        auth_status["details"] = result.stdout
    except subprocess.CalledProcessError as e:
        auth_status["status"] = "failed"
        auth_status["details"] = e.stderr
    except Exception as ex:
        auth_status["status"] = "terminated"
        auth_status["details"] = str(ex)

@app.route('/', methods=['GET', 'POST'])
def home():
    terraform_code = ""
    user_query = ""
    input_fields_html = ""

    if request.method == 'POST':
        user_query = request.form.get('query', '')

        base_prompt = (
            "Generate modular Terraform code using best practices. "
            "Create separate files for main.tf, vm.tf, vars.tf, terraform.tfvars, subnet.tf, kubernetes_cluster etc. "
            "Ensure the code is clean and execution-ready. "
            "Use markdown headers like ## Main.tf: followed by code blocks."
        )

        full_prompt = base_prompt + "\n" + user_query
        try:
            response_cleaned = generate(model='codegemma:7b', prompt=full_prompt)
            terraform_code = response_cleaned.get('response', '').strip()
        except Exception as e:
            terraform_code = f"# Error generating code: {str(e)}"

            provider_block = f"""
              provider "azurerm" {{
              features {{}}
              subscription_id = "Enter your credentials here."
              client_id       = "{CLIENT_ID}"
              client_secret   = "{CLIENT_SECRET}"
              tenant_id       = "{TENANT_ID}"
            }}"""
            terraform_code = provider_block + "\n\n" + terraform_code

        with open('main.tf', 'w', encoding='utf-8') as f:
            f.write(terraform_code)


        # Create output directory
        output_dir = r"C:\Users\riya.achkarpohre\Desktop\AI\test7\terraform_output"
        os.makedirs(output_dir, exist_ok=True)

        # Define output paths
        paths = {
            "main.tf": os.path.join(output_dir, "Main.tf"),
            "vm.tf": os.path.join(output_dir, "VM.tf"),
            "subnet.tf": os.path.join(output_dir, "Subnet.tf"),
            "vpc.tf": os.path.join(output_dir, "VPC.tf"),
            "vars.tf": os.path.join(output_dir, "Vars.tf"),
            "terraform.tfvars": os.path.join(output_dir, "Terraform.tfvars"),
            "kubernetes_cluster.tf": os.path.join(output_dir, "kubernetes_cluster.tf")
        }

        # Split response using markdown headers
        sections = re.split(r'##\s*(.*?)\.tf:\s*\n+```(?:terraform)?\n', terraform_code)

        # sections = ['', 'Main', '<code>', 'VM', '<code>', ...]
        for i in range(1, len(sections), 2):
            filename = sections[i].strip().lower() + '.tf'
            code_block = sections[i + 1].strip()

            # Remove closing backticks if present
            code_block = re.sub(r'```$', '', code_block)

            # Save to file if path is defined
            if filename in paths:
                with open(paths[filename], 'w', encoding='utf-8') as f:
                    f.write(code_block)
                    print(f"\n--- Written: {filename} ---")
                    print(code_block)
            else:
                print(f"\n--- Skipped unknown file: {filename} ---")

        return render_template_string(f"""
        <html>
        <head><title>Terraform Generator</title></head>
        <body>
            <form method="post">
                <center>
                    <label>Enter your query:</label><br>
                    <textarea name="query" rows="6" cols="80" placeholder="Describe your infrastructure requirement here..."></textarea><br><br>
                    <input type="submit" value="Generate Terraform">
                </center>
            </form>
            <hr>
            <h2>Generated Terraform Code:</h2>
            <pre>{terraform_code}</pre>
            <h2>Enter values for the required variables:</h2>
            <h2>Authentication Status:</h2>
            <pre>Status: {auth_status['status']}\n{auth_status['details']}</pre>
        </body>
        </html>
        """)

    # Initial GET request
    return render_template_string('''
    <html>
    <head><title>Terraform Generator</title></head>
    <body>
        <form method="post">
            <center>
                <label>Enter your query:</label><br>
                <textarea name="query" rows="6" cols="80" placeholder="Describe your infrastructure requirement here..."></textarea><br><br>
                <input type="submit" value="Generate Terraform">
            </center>
        </form>
    </body>
    </html>
    ''')

authenticate_with_azure()
@app.route('/authenticate', methods=['POST'])
def authenticate():
    authenticate_with_azure()
    return jsonify(auth_status)

if __name__ == '__main__':
    app.run(debug=True)

Open Visual Studio, create a new file named file.py, and paste the code into it. Then, open the terminal and run the script by typing:

python file.py

Flask Development Server

Code Structure Explanation

• Azure Authentication
  • The app uses the Azure CLI (az.cmd) via Python’s subprocess.run() to authenticate with Azure using a service principal. This ensures secure access to Azure resources before generating Terraform code.
• User Query Handling
  • When a user submits a query through the web form, it is captured using:

user_query = request.form.get('query', '')

• Prompt Construction
  • The query is appended to a base prompt that instructs CodeGemma to generate modular Terraform code using best practices. This prompt includes instructions to split the code into files, such as main.tf, vm.tf, subnet.tf, etc.
• Code Generation via CodeGemma
  • The prompt is sent to the CodeGemma:7b model using:

response_cleaned = generate(model='codegemma:7b', prompt=full_prompt)

• Saving the Full Response
  • The entire generated Terraform code is first saved to a main.tf file as a backup.
• Output Directory Setup
  • A specific output directory is created using os.makedirs() to store the split .tf files:

output_dir = r"C:\Users\riya.achkarpohre\Desktop\AI\test7\terraform_output"

• File Path Mapping
  • A dictionary maps expected filenames (such as main.tf and vm.tf) to their respective output paths. This ensures each section of the generated code is saved correctly.
• Code Splitting Logic
  • The response is split using a regex-based approach, based on markdown headers like ## main.tf: followed by Terraform code blocks. This helps isolate each module.
• Conditional File Writing
  • For each split section, the code checks if the filename exists in the predefined path dictionary:
    • If defined, the code block is written to the corresponding file.
    • If not defined, the section is skipped and logged as  “unknown file”.
• Web Output Rendering
  • The generated code and authentication status are displayed on the webpage using render_template_string().

Terminal

The Power of AI in Infrastructure Automation

This project demonstrates how combining AI models, such as CodeGemma, with simple tools like Flask and Terraform can revolutionize the way we approach cloud infrastructure provisioning. By allowing developers to describe their infrastructure in natural language and instantly receive clean, modular Terraform code, we eliminate the need for repetitive manual scripting and reduce the chances of human error.

Running CodeGemma locally via Ollama ensures:

• Full control over data
• Zero cost for code generation
• Fast and private execution
• Seamless integration with existing workflows

The use of Azure CLI authentication adds a layer of real-world applicability, making the generated code deployable in enterprise environments.

Whether you’re a cloud engineer, DevOps practitioner, or technical consultant, this tool empowers you to move faster, prototype smarter, and deploy infrastructure with confidence.

As AI continues to evolve, tools like this will become essential in bridging the gap between human intent and machine execution, making infrastructure-as-code not only powerful but also intuitive.

Perficient is proud to be included in the IDC ServiceScape: Worldwide and U.S. Microsoft Power Apps Low-Code/No-Code Custom Application Development Services, 2025 (Doc# US53748825 September 2025) report. We believe this inclusion highlights our commitment to helping enterprises accelerate innovation and streamline development through Microsoft Power Platform.

This IDC ServiceScape offers a comprehensive guide on the key capabilities of custom application development service providers using the Microsoft Power Apps low-code/no-code development platform, featuring services from companies including Perficient. The status of each service capability is categorized as fully supported, partially supported, partner provided, road map, or not supported, aiding services buyers in quickly identifying which vendors align with their changing requirements.

Powering Innovation with Microsoft Power Platform

As digital transformation accelerates, low-code/no-code platforms are becoming essential tools for agility and innovation. Perficient is proud to be included in this evolving landscape and remains committed to delivering solutions that drive real business outcomes.

“Our approach to Power Platform is rooted in strategy, scale, and speed. We’re not just building apps—we’re enabling transformation. By combining governance frameworks, multi-shore delivery, and AI-powered experiences, we help clients unlock the full potential of low-code development and drive meaningful business outcomes.” – Eric Schmitt, Director of Microsoft Business Applications.

Perficient offers a comprehensive suite of low-code/no-code services designed to accelerate transformation:

• App modernization programs to migrate legacy systems to Power Platform
• Intelligent automation and rapid RPA migration (e.g., UiPath to Power Automate Desktop)
• Custom Copilot envisioning workshops and enterprise app development
• Governance engagements including CoE setup and citizen developer enablement
• Process mining and lifecycle management
• Multi-shore delivery models with agile development pods and managed services

We’re also increasing investment in Copilot Studio Agents, helping clients build custom functionality and deploy agents within Power Platform environments. Our governance frameworks ensure scalable, secure adoption—whether you’re enabling citizen developers or launching enterprise-wide automation programs.

Learn more about our Power Platform capabilities: Power Platform / Perficient

Perficient is a global digital consultancy with over 7,000 colleagues worldwide, operating as one unified team across North America, LATAM, and India. With deep expertise in industries like Healthcare & Life Sciences, Manufacturing, and Automotive, we deliver strategic technology solutions that drive measurable outcomes. Our Microsoft practice is backed by more than 25 years of experience and over 250 certified cloud consultants, with strong capabilities in Azure, M365, Dynamics CRM, and Power Platform.

Perficient differentiates through global delivery, scalability, and robust governance. With 95% of our business coming from repeat clients, we’re proud to be a trusted partner in building AI-first, low-code solutions that deliver real business value.

Ready to move from ambition to impact? Let’s define your low-code strategy and build the foundation to lead what’s next.

Salesforce continues to evolve its digital experience capabilities by embedding artificial intelligence across its platform. Forrester’s report, The Impact of AI on Digital Experience Platforms, discusses how vendors like Salesforce are integrating agentic AI and Generative AI (GenAI) to streamline experience operations and empower practitioners. 

With tools like  Agentforce, Salesforce is moving beyond traditional automation to deliver intelligent, connected experiences. These innovations are designed not only to enhance customer engagement but also to support the practitioners behind the scenes — enabling smarter orchestration, faster decision-making, and more efficient workflows. 

Agentic AI Unifies Data and Drives Action

Salesforce’s agentic AI capabilities are designed to simplify complex orchestration across its ecosystem. These intelligent agents help practitioners navigate vast feature sets, automate routine tasks, and unlock insights from unified customer data. 

Perficient’s Salesforce Consulting Managing Director Megan Glasow has seen growing interest in these capabilities, especially as organizations look to consolidate their tech stacks and reduce friction in experience delivery. 

“Salesforce’s consolidation of DXP components paired with tools like Agentforce is helping clients streamline orchestration and unlock hidden data. We’re guiding them through this transformation with a focus on integration and measurable outcomes,” said Glasow.  

Unlocking Business Potential With Perficient and Agentforce. Get the Guide

Using GenAI From Content to Code

Salesforce’s GenAI tools are also enabling marketers to generate personalized content, optimize campaign strategies, and even build applications with minimal coding. These capabilities help teams move faster and deliver more relevant experiences across customer journeys, but speed alone isn’t the goal. As Glasow explains, success with GenAI depends on thoughtful implementation and alignment with business strategy. 

She said, “We’re helping clients explore how GenAI can reduce manual effort and accelerate personalization. But it’s not just about speed. It’s about aligning AI with business goals and ensuring responsible use.” 

Driving Innovation with Responsible AI Adoption

Successful AI adoption in DXPs requires more than just technology. Organizations must invest in strong data foundations, human oversight, and change management to ensure responsible and effective use of AI. These are areas where we continue to guide clients with strategic consulting and hands-on implementation. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Salesforce. Whether it’s integrating predictive analytics, deploying cognitive copilots, or improving data governance, our teams are leading the way in enabling AI-powered transformation. 

If you’re exploring how to bring AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

See How AI Drives Business Outcomes at Dreamforce 2025

At Dreamforce 2025, teams will demonstrate how AI-powered agents and unified data accelerate decision-making, improve adaptability, and deliver measurable results. Attendees can explore how organizations turn strategy into execution through exclusive experiences, including a happy hour, a keynote watch party, a tasting event, and personalized strategy sessions. 

These events highlight how AI enables leaders to streamline operations, reduce inefficiencies, and maximize return on investment. Visit the event landing page for full details and discover how to lead with confidence in an AI-first business environment. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Salesforce expertise here.  

Contact us to learn more.