Q&A: Cognizant Moment on the 'Agency-as-Software' Model

According to Ben Wiener, Senior Vice President and Global Head of Cognizant Moment, the traditional agency model is beginning to break down. 

Instead, he predicts that a new model is emerging – termed “agency-as-software”. As technology begins to automate more marketing tasks, Ben says that agencies are shifting towards being “always on systems,” meaning that the value of a marketing agency shifts towards human judgement, strategic thinking and creativity. 

In conversation with Marketing Chief, Ben explains how this new approach is transforming the way agencies operate and the role of human expertise in a more AI-enabled industry. 

What happens when AI agents, not people, are doing the bulk of discovering, comparing and recommending products, and how does that change the role of an agency?

As AI agents take on a greater role in researching, comparing and recommending products and services, brands will need to respond more quickly to changes in customer preferences, competitor activity and market conditions.

The challenge is that many organisations still operate through planning cycles, campaign timelines and decision-making processes that were designed for a slower-moving environment. When customer behaviour, competitive positioning and buying signals can change in near real time, those approaches can struggle to keep up.

That changes the role of agencies. Traditionally, agencies have been judged by the campaigns and outputs they produce. Increasingly, their value will come from helping organisations build marketing operations that can adapt continuously as customer behaviour, competitor activity and market conditions changes. 

In practice, that means spending less time managing individual campaigns and more time helping clients connect insight, execution and measurement so marketing can respond more quickly as new information emerges.

How do traditional agency setups work in the age of AI?

Most agency models were traditionally built around specialist teams working in sequence. Research informs strategy, strategy informs creative development and campaigns are delivered through a series of handovers, approvals and production processes.

AI changes the economics of that model. Tasks that once required significant time and resource can increasingly be automated, while clients expect faster delivery, greater transparency and a clearer connection between investment and business outcomes.

 As a result, value is moving away from managing processes and producing deliverables. It is moving towards areas where human judgement remains essential, including understanding customer behaviour, making strategic decisions, applying creativity and ensuring technology, data and execution work together effectively.

AI can make delivery more efficient, but it cannot replace judgement. Understanding customers, making strategic decisions and applying creativity remain fundamentally human responsibilities.

Cognizant Moment works with global brands like Mars and the FA. What unique challenges do organisations like this face when trying to embed AI directly into their marketing and customer experience architecture?

Five challenges consistently come up with our clients and engagements, and each points to something specific about how the Agency-as-Software model addresses them.

Brand quality at volume

AI makes it possible to produce significantly higher volumes of marketing content, but volume without quality is a liability, not an advantage. What we help clients build is the discipline to match that output with rigorous evaluation: synthetic personas, pre-market testing, performance feedback loops. The goal is always resonance, not throughput. The brands that get this right are the ones that treat AI as a way to produce better work faster, not simply more of it.

Responsible personalisation

​​​​​​​ The opportunity to engage customers in real time, at scale, with genuinely personalised content is real. So is the risk. Personalisation can miss, and when it does it damages the relationship it was meant to strengthen. Responsiveness at speed also means fewer manual checks in the process. Organisations need frameworks that let them move quickly while ensuring every interaction remains appropriate for the customer it reaches.

Degrees of autonomy

Agentic AI is powerful, but the question of what to automate and what to keep human is one our clients are actively working through. There is no single answer. The right model depends on the stakes of the decision, the maturity of the data and the level of brand risk involved. What we provide is a framework for making those choices deliberately, and for deploying the extraordinary creative and marketing talent our clients already have in the places where human judgement genuinely matters most.

Governance and risk

The organisations making real progress are not the ones that move fastest. They are the ones that move with confidence, because they have the governance frameworks, validated technology partnerships and engineering maturity to back it up. Clients are looking for partners who understand that operating responsibly in this environment is as important as operating effectively within it.

From fragmentation to orchestration

The market is offering organisations more capability than they have ever had access to. What it is not offering them is coherence. Endless technology and point solutions risk compounding the fragmentation they were meant to solve. Our role is orchestration: helping clients bring intelligence, content, execution and measurement together into a connected system oriented around business outcomes and customer experience. The technology is a means, not the answer.

What do ‘always-on systems’ look like in practice, and how can they replace traditional operating models in marketing?

Always-on systems replace a model built around individual campaigns, projects and handovers with one where insight, content creation, execution and measurement are connected.

That is the idea behind Agency-as-Software. Customer and market intelligence feeds AI content generation engines, which in turn power campaign delivery and personalised customer engagement. Every interaction then generates new data that helps optimise future activity, creating a continuously learning system that improves over time.

In practice, marketing becomes an ongoing process of learning and optimisation. Insights inform content creation and delivery, performance data feeds into future decisions and activity can adapt continuously as customer behaviours, preferences and market conditions change.

The result is a marketing operation that is always active, always learning and able to adapt as new information becomes available, rather than waiting for the next planning cycle or campaign launch.

As AI takes on a bigger role in marketing, is there still value in human insight?

One of the biggest misconceptions about AI is that it reduces the importance of human expertise. In reality, it makes it even more important.

As execution becomes easier to automate, the things that differentiate successful organisations become harder to replicate. Understanding what matters to customers, identifying opportunities worth pursuing, defining a brand's position in the market and making informed decisions about where to invest all rely on judgement, experience and perspective.

That means strategic thinking, creative judgement and a deep understanding of customer behaviour become even more valuable. As more of the execution becomes automated, the value agencies provide increasingly comes from helping clients make informed decisions about where to focus, what opportunities to pursue and how to respond to change.