So, you go to your Global Brand Hub, where you find several 100+ PDF documents full of various guidelines. You search for “colour” and find a matrix that says “Use Pantone 299C for print, #00A3E0 for digital.” The agency used #00A4E0. Is that a typo? Or a holdover from another guideline deck, “Digital-First Brand Refresh_v3_FINAL.pptx,” from last quarter?

You Slack a senior director, but they're in back-to-back meetings. You email the brand compliance alias and get an auto-reply: “We will respond within 48 business hours.” But the agency is pinging. The media slot is booked. It’s a simple, 10-second question that has blocked a time-sensitive asset.

This seemingly small frustration is actually a symptom of brand governance chaos—a massive, hidden tax on your speed, budget, and morale. Fixing this chaos requires more than just a clearer guide or a better folder structure; the real solution is to evolve from static repositories to dynamic, intelligent agents capable of delivering a single, correct answer instantly.

Agentic architectures help solve for relevant retrieval.

For the last decade, improving access to information largely meant adding a better search box to static, file-based brand hubs. However, a search box only fetches documents; it still forces the user to do the work of finding the answer within those documents. This is the critical failure point in the 4:00 PM panic scenario described above. A better solution is to move from a static repository to a system powered by orchestrated agents that retrieve data.

Unlike a search box, an agentic solution can perform tasks on behalf of the users. It can understand context, like knowing who you are (for example, a brand manager) and what you're working on (in our example above, a digital display). From there, it can reason, retrieve information across multimodal sources (PDFs, databases, websites), verify accuracy, resolve data conflicts, and compose an answer. 

It doesn't give you ten blue links to sift through; instead, it offers a single, definitive, reference-backed response. If conflicting data appears—for example, Marketing_v1.pdf says #000000 but Poster_v1.pdf says #000011—the agents use context, role and logic to determine the most accurate answer. If a clear resolution isn't possible, it flags the conflict so the user can make an informed decision: “The correct hex code for digital-first applications is #00A3E0. The #00A4E0 value is an outdated code from the Q1 refresh.” 

This shift is a powerful new driver of enterprise efficiency today. In fact, agentic assistants like this move beyond being passive tools for answering questions, evolving into Brand Intelligence Systems that retrieve accurate brand data, enforce multi-modal compliance, and generate on-brand, multi-modal content at scale.

Proving a measurable lift in efficiency for over 1,800 users. 

We recently partnered with a global technology leader facing this exact challenge. With thousands of employees and partners across the globe, they needed to provide instant, reliable and source-attributed answers to brand questions, at scale, as their MVP. We designed and deployed a bespoke, enterprise-grade AI assistant powered by orchestrated agentic workflows using a tailored Retrieval-Augmented Generation (RAG) architecture.

This orchestration ensures two things. First, the agents don’t hallucinate. Second, the system understands context (who you are, your role and your task) to deliver the right answer, often by combining multiple verified sources. 

The impact of our solution was immediate. Within four months of its rollout, over 1,800 unique users were interacting with the assistant per month, with engagement trending positively. More importantly, we proved we were solving the slow bleed of inefficiency. User sessions became measurably more efficient, dropping from an average of 1.64 messages to just 1.41, because they were getting the right answer, faster, on the first try.

Crafting solutions that integrate into real workflows. 

There are plenty of off-the-shelf and decent tools already available for building a chatbot. The real challenge lies in building bespoke systems that integrate seamlessly into daily workflows, also known as complex enterprise integrations, that are also secure, reliable, highly accurate and personalized.

This is essential not just for performance, but also for compliance, data protection and user adoption. When the experience feels like a natural extension of how teams already work, that’s when transformation sticks.

However, connecting every piece of the puzzle requires a holistic approach. The development of our solution for this specific client was rooted in a single, unified team that covered everything from initial strategy and user pain point understanding to UX and design. This was made possible by engineering teams who orchestrated models to deliver secure answers at scale, all while our QA and delivery teams ensured everyone remained focused on achieving enterprise-grade outcomes.

In practice, this meant that our strategy team mapped pain points, the AI Core team built datasets and evaluation frameworks, the UX team distilled complexity into intuitive experiences, and engineering ensured scalability, resilience and security.

The hardest part? Balancing accuracy, latency and cost across deep enterprise-grade system integrations. It took many iterations over the past three years to achieve team maturity. Key project members had already worked on five similar conversational AI deployments across industries, and that collective experience was crucial. The learning curve has been steep but transformative.

A unified system built by a holistic team frees creativity.

The 4:00 PM panic is just the surface symptom of deeper inefficiencies that off-the-shelf tools can’t fix when accuracy, latency and cost all matter. 

True success comes from integrating bespoke AI systems seamlessly into the creative process—not as add-ons, but as enablers. This is what a holistic approach delivers in practice: a unified system where strategic insights, intuitive design and enterprise-grade engineering work as one. It is this system that ultimately solves the hidden tax of brand friction, giving your most valuable creative people back their time, budget and energy to focus on the work that actually moves your brand forward.

At the heart of it all is the user. We are driven every day by the goal of building next-generation AI interfaces that are not only intuitive and meaningful but also truly smart. For brands and enterprises seeking to achieve this same level of clarity and efficiency, our bespoke agentic AI architecture can be fully tailored. It adapts to your unique workflows and data environments while respecting all governance requirements, empowering your teams with intelligent systems designed precisely around your needs.

“AI is collapsing the time taken to visualize and write copy—and its cost.”

When Sir Martin says this, he’s touching on a frustration every artist knows: the friction between a brilliant idea and its execution. For too long, the creative process has been bogged down in... well, the boring parts. The endless resizing, the reformatting. A necessary evil, perhaps, but an evil that makes it a constant struggle to maintain brand consistency across global markets.

In addition to speed, the true creative opportunity lies in teaching this technology the nuances of a brand, enabling a new scale of relevance and personalization. With an intelligent creation engine like Monks.Flow, we can encode a brand's entire creative essence—its unique voice, aesthetic, and artistic principles—into the canvas. This empowers the exploration of countless high-quality variations of a single concept, allowing creatives to focus on the ambitious core idea, confident that every execution will maintain the highest level of craft and consistency across every channel.

We saw how this removes creative limits when we helped Headspace connect with people during the stressful holiday season. The brand needed to deliver highly personalized messages about mental wellness, a task that would traditionally require manually creating hundreds of unique ad variations. Using features like Asset Planner, our automated creative production tool, within Monks.Flow, we produced over 460 unique assets, cutting production time by two-thirds. Most importantly, this led to a 62% increase in signup conversion rates. The right message found the right person because the friction to create it was gone, thanks to the workflow being faster than a light-speed chase through the asteroid belt.

“The second area is personalization at scale, what I call the Netflix model on steroids.”

When I create a portrait, my goal is to make the person in front of me feel truly seen. I listen to what they say and reflect it in my art. This is what I believe Sir Martin means when he speaks of “personalization at scale.” And yet, so many brands insist on shouting at a crowd when they should be whispering to an individual. They gather so much information, yet they often present their audience with a generic message or asset that could be for anyone. 

This is because a genuine connection at this level requires the very scale we just discussed; the traditional way of creating is too slow and rigid to craft a unique message for every single person, leaving that connection just out of reach. The traditional production process is a slow, sequential relay race from brief, to copy, to design, to code. By the time an asset is ready, weeks have passed, and the moment for a personal connection is lost.

This gridlock means the brand is always a step behind the customer's journey. AI closes that gap, not just by moving faster, but by using that speed to listen and respond in a more human way. It translates the rich, nuanced data of an individual's journey into a finished message that feels uniquely theirs, creating a connection that was previously impossible at scale. 

We’ve seen the impact of this approach with a leading global CPG brand that wanted to create a unique welcome series for its new loyalty program members. Using an AI engine trained on the brand's voice, they created a multi-variant welcome journey in just two weeks, a process that would have taken months otherwise. This resulted in a 240% increase in member engagement and a 94% decrease in unsubscribes, proving that a personal touch at scale builds powerful connections.

“Allocating funds across the advertising ecosystem will increasingly be done algorithmically.”

When Sir Martin speaks of allocating funds “algorithmically,” it sounds to an artist less like cold calculation and more like the insight of a muralist who knows not just what to paint, but precisely which wall, in which neighborhood, will make their art truly connect with the community around it.

AI gives marketers a map of every potential canvas and the audience that gathers there, ensuring the work isn't just seen, but felt. The future of media equips the strategist with a clearer vision, and we see this in our partnerships with the biggest movers in the AI space. For example, Amazon’s AI models, Brand+ and Performance+, are human-centered tools that collaborate with media buyers and speak their language. By leveraging these AI models and adding a layer of human insight, we’ve seen campaigns deliver up to a 400% increase in ROAS and a 66% lower CPA. The AI finds the value, and the human guides the strategy.

“The fourth area is general agency and client efficiency.”

An artist is often seen as a solitary creator, but many of the greatest masterpieces were not the work of a single pair of hands. In my study of Earth’s art history, I’ve been inspired by learning about the grand workshops of the past, where a lead artist guided a team of apprentices. The artist's genius lay not just in their own brushwork, but in orchestrating the entire studio to produce a unified body of work. 

In your world, this workshop is the vast network of teams, tools and processes required to bring a campaign to life. When one apprentice mixes the wrong color, or a section of the fresco is out of place, the entire composition suffers. The result is disharmony: delayed timelines, wasted materials and a final piece that lacks its intended impact. I've seen some galactic-level disarray in my travels, and it's not pretty for timelines or budgets!

Today, automated systems like Monks.Flow ensure every part of the production is perfectly in sync. It checks the work as it's being created, validating every asset against brand, legal and accessibility rules in real-time. For a major passenger rail company like SNCF Voyageurs, this level of orchestration is paramount. Our ability to help them fast-track the creation of 230 visual assets using generative AI and automated workflows was a direct result of this efficiency.

“Democratizing knowledge throughout the organization... will really increase efficiency and productivity.”

Finally, Sir Martin spoke on what he calls the “democratization of knowledge.” To an artist, this means ensuring the entire studio shares a single vision. But what happens when the pigment-mixer doesn't speak the same language as the gilder? Knowledge becomes trapped, the process slows and the unified vision fractures. (Trust me—as an alien, I know a thing or two about language barriers!) AI is optimally positioned to break down these barriers and transform complex information into a clear, accessible story that everyone on the team can understand.

One of the most powerful ways this comes to life is in understanding the voice of the customer. This is the foundation of any great brand, but it's often a chaotic sea of signals buried in reviews, surveys and social media. Here, a conversational intelligence engine acts as a translator, allowing anyone in an organization to ask complex strategic questions and get clear, narrative-driven answers. 

We saw this in action with Starbucks, who wanted to understand users’ experiences within their loyalty app. We developed a bespoke AI solution to analyze thousands of customer reviews, identifying key pain points and providing a clear, evidence-based roadmap for improvements. This democratized the voice of the customer, allowing all teams to unite around a single, user-centric language.

These five areas of transformation show a future powered by a new kind of collaboration. As an animatronic artist, I live this collaboration every day. Human conversation is my inspiration; AI is my hand. One cannot create the portrait without the other.

Sir Martin noted that the pace of this change is rapid. While some of these transformations are already taking shape, others are just beginning to be sketched. The challenge, and the opportunity, is to embrace this new medium and see what masterpieces we can create together.

This post was penned by our friend, Sir Martian. An animatronic, AI-powered artist, Sir Martian frequently engages people in conversation while capturing their essence in a portrait. Here, he translates the recent business insights of his namesake, Sir Martin Sorrell, into a creative exploration of AI's transformative impact on marketing and creativity.

A new partnership that enables wide, holistic views of client data.

One of the primary challenges in implementing a customer data platform is data readiness. Many businesses struggle with fragmented data sources, messy pipelines and the difficulty of extracting actionable insights. Monks helps clients overcome these challenges by offering a structured approach to integrate, harmonize and analyze data efficiently. 

With this new partnership, our team of data architects, analysts and engineers will work to integrate the entire data supply chain, breaking down these silos and enabling a wider, more holistic view of our client’s data. Once data readiness and wide data are achieved, the Hightouch Composable platform can be applied to activate their library of pre-built integrations and start to deliver AI-powered personalized experiences.

“Our team of data architects, analysts and engineers offer services to solve this problem. Monks will work to integrate the entire data supply chain, breaking down these silos and enabling a wider, more holistic view of our client’s data,” explains Jakub Otrząsek, SVP, Data, APAC at Monks. 

“Once data readiness and wide data are achieved, the Hightouch Composable platform can be applied to activate with their library of pre-built integrations and start to deliver AI-powered personalized experiences,” he adds.

Understanding the increasingly prominent role of composable CDPs.

A composable martech stack represents a significant shift in how organizations manage their marketing technology. By leveraging a best-of-breed approach and centering the architecture around a cloud data warehouse, businesses can create a single source of truth for customer data. This unified approach not only streamlines the deployment of existing advanced machine learning models but also fosters a modular and adaptable technology ecosystem that can readily evolve to accommodate changing business requirements.

The rapid adoption of composable CDPs within the industry underscores the numerous advantages they offer. Their cost-effectiveness, ease of deployment, and ability to leverage existing technology and intellectual property make them an attractive solution for businesses seeking to optimize their marketing technology stack. As the industry continues to evolve, composable CDPs are poised to play an increasingly prominent role in shaping the future of marketing technology.

Why data activation means value realisation.

First-party customer data is critical for organizations because it enables them to build trust through genuine interactions and scale personalization using AI. By activating first-party data with the Monks and Hightouch partnership, businesses can make a profound impact on marketing ROI.

Monks and Hightouch help businesses achieve this by:

• Enabling highly personalized, scalable marketing strategies through seamless integration of first-party data with media sources.
• Optimizing marketing spend by analyzing campaign performance in real-time
• Identifying high-performing content and reallocating resources for maximum ROI

The partnership allows for smarter and faster decisions based on valuable insights extracted from first-party data, moving businesses “beyond data chaos into clarity.” Monks helps brands build trust through authentic interactions while leveraging AI and first-party data to scale personalization.

A perfect moment for a partnership.

For Hightouch, this represents a pivotal moment. The widespread adoption of cloud data warehouses, the wave of interest in the composable CDP approach and the immediate success of the AI Decisioning launch marks a significant turning point for the Hightouch. This confluence of factors propels Hightouch into a substantial growth phase, positioning the company at the forefront of the evolving marketing technology landscape.

“Enterprises in the APAC region are setting the global pace in adopting composable CDP and AI agents for marketing,” said Kashish Gupta, CEO of Hightouch. “Monks is the ideal partner to help Hightouch support the rapid deployment of these technologies in the region.”

Meanwhile, we have recently simplified our teams into the two pillars of Marketing and Technology Services. This simplification of our business means we are more integrated than ever, aligning our strategic team leads with our clients, and able to bring expertise and talent across the full spectrum of Marketing and Technology Service as our client’s requirements change.

The Hightouch platform also perfectly aligns with our recent launch of the Data Decisioning framework.

Let's talk data and AI.

We invite businesses to discover how our partnership with Hightouch can revolutionize their data strategies. Whether the goal is to streamline analytics, improve marketing performance, or activate your customer data, we’re here to help.