Kooba on Agentic Workflows: Why Strategy and Creativity Still Define Great Agencies
How Kooba is using agentic AI to automate execution while doubling down on the human creativity and strategic thinking that brands can’t afford to lose.
“Clients rely on strategic thinking and outside perspective. AI can support the work—but it can’t create what makes brands truly stand out.”
Elena Rimeikaite, Design Director of Kooba
As AI becomes increasingly capable of generating content, producing designs, and automating complex workflows, it’s easy to assume that creativity itself is becoming automated.
Kooba sees the future differently.
The agency believes AI will continue transforming how work gets done but not why it matters. As more businesses gain access to the same technologies, competitive advantage shifts away from execution and toward originality, strategic thinking, and the ability to create experiences that genuinely differentiate a brand.
For Kooba, agentic AI isn’t replacing creativity. It’s creating more room for it.
Agency Snapshot
🧠 Agentic Maturity
Pilot-stage agentic workflows with department-specific AI agents coordinated through strategic human oversight.
⚙️ Primary Use Cases
Research, reporting, operational efficiency, and cross-functional collaboration.
🌍 Industries
SaaS & Tech
🧩 Core Tech Stack
OpenAI (GPT-4o, o1, etc.), Anthropic (Claude 3.5 Sonnet/Opus)
How Autonomous Are Today’s Agentic Workflows?
While fully autonomous systems continue to attract attention, most agencies—including Kooba—continue to rely on human-guided workflows, particularly when creativity and strategic decision-making are involved.
How Agentic Workflows Are Structured at Kooba
Kooba’s approach reflects an important evolution in how agencies organize expertise.
Traditionally, projects moved between multiple departments, with specialists reviewing work at each stage before handing it off to the next team.
Today, many of those departmental functions are supported by specialized AI agents. Instead of requiring human contributors at every operational step, the agency increasingly relies on intelligent systems to represent specific disciplines while assigning a dedicated strategist responsibility for overseeing the entire workflow.
Although this model is currently being tested across selected pilot projects, it illustrates how agentic AI can simplify collaboration without removing strategic ownership from the process.
Rather than replacing departments, AI enables them to work together more efficiently through a coordinated operating model.
Inside the Workflow: From Input to Output
Within Kooba’s pilot workflows, specialized AI agents support different functional areas throughout a project.
Research activities, reporting tasks, and operational coordination are distributed across agents designed to replicate the responsibilities traditionally handled by individual departments.
Rather than passing work through multiple human teams, information flows between specialized agents before reaching a strategic lead who evaluates recommendations, provides business context, and determines the final direction.
This significantly reduces operational overhead while preserving the quality of strategic decision-making.
Instead of removing expertise, the workflow concentrates it where it creates the greatest value.
The Role of Human Oversight
Despite reducing the number of operational review stages, Kooba has no intention of removing people from the process altogether.
In fact, the agency believes human involvement becomes even more important as automation increases.
As AI agents assume greater responsibility for execution, strategists shift their focus toward creative thinking, brand differentiation, and long-term decision-making—areas where experience, intuition, and outside perspective remain difficult to automate.
For Kooba, AI doesn’t eliminate the need for experts. It raises the value of expertise.
A Real-World Use Case
One of Kooba’s most successful implementations of agentic AI has focused on research and reporting.
By assigning repetitive analytical tasks to specialized agents, the agency has significantly reduced the time required to gather information, prepare reports, and support client engagements.
The workflow has improved operational efficiency while reducing the number of manual hours required for routine activities.
More importantly, it has allowed consultants to spend less time producing reports and more time interpreting what those reports actually mean for clients.
Although the agency continues to test this model through pilot projects, the early results reinforce a core principle: automation creates the greatest value when it increases the time available for strategic thinking.
Key Advantages of Agentic Workflows
For Kooba, the greatest benefit of agentic AI lies in creating space for higher-value work.
By reducing repetitive operational tasks, specialists gain more time to focus on creativity, innovation, and solving complex business challenges.
Efficiency matters but only because it allows people to invest their expertise where it has the greatest impact.
Rather than measuring success by the number of tasks automated, Kooba measures success by the quality of thinking automation makes possible.
Challenges and Limitations
Kooba believes one of the greatest long-term risks associated with AI is creative convergence.
As more organizations rely on similar tools and increasingly standardized workflows, brands may begin producing work that feels technically correct but strategically indistinguishable.
The agency has already observed recurring design patterns emerging from AI-assisted production and believes businesses that rely too heavily on automation risk blending into an increasingly crowded marketplace.
This makes human creativity not less important, but more valuable than ever.
How Agentic AI Is Reshaping Agency Models
Kooba believes clients will continue adopting AI internally, but that shift will ultimately reinforce rather than diminish the role of strategic agencies.
While businesses can automate production and operational tasks, they still need external partners capable of challenging assumptions, identifying opportunities, and creating distinctive brand experiences.
Technology may become widely available.
Original thinking does not.
As execution becomes increasingly commoditized, agencies differentiate themselves through perspective, creativity, and the ability to build brands that stand apart from the growing sea of AI-generated sameness.
Conclusion
For Kooba, agentic AI is not a replacement for creativity.
It is a catalyst for it.
By allowing intelligent systems to handle routine execution while people focus on strategy and originality, the agency demonstrates that the future of creative work is not about choosing between humans and AI but about ensuring each contributes where they create the greatest value.
Because in a world where everyone has access to the same technology, differentiation will belong to those who think differently.
