Artificial Intelligence as an Enabler for Business Agility

Demand for agility is being drowned by the heightened rate of innovation in Artificial Intelligence, and this is expected due to a myriad of reasons, including the fear of missing out (FOMO). As a consultancy that championed several organisational transformational initiatives, we see the adoption of AI in many organisations as just one more unpredictable factor in the already complex world of work, and we are not fazed by it.

We consider AI adoption an enabler for business agility, and in this short post, we discussed how AI can be such an enabler.

1. Empowered and Smaller Teams

As part of organisational transformational initiatives, we support organisations in restructuring into smaller, cross-functional, and self-managing teams. The Scrum Framework suggests an ideal team size of less than 10 people, and as team members can now augment their skills with AI, we see an opportunity for smaller teams.  In this article, Jeroen Egelmeers describes AmpCoding as an alternative to Vibecoding. We see various possibilities, from Product Developers ampcoding to Product Developers as orchestrators of an entire Team of AI Agents. 

Some of the use cases that we have tried include providing large language models with product briefs and HTML design. The LLM generates potential test cases that humans can then review, a previously reserved task for team members with testing skills. 

2. Shorter Iteration with Functional Mockups

Until recently, Product Owners paired up with User Interface / User Experience Designers to create high-fidelity designs that could be used to test ideas with potential product users. Testing ideas with functional and clickable mockups but this is most likely considered as an expensive upfront cost for more teams that we work with but with tools such as Replit and lovable; Product Manager can use these AI code generator to build functional mockups that can be used for user testing without taking away from development time. 

These tools will reduce the time taken to create throwaway and usable prototypes. This will have a massive impact on the team’s effectiveness, as it should help reduce the chances of building a product nobody wants.

3. Improved Code Quality

Many years ago, some of our consultants were able to introduce technical practices from eXtreme programming to our clients, such as TDD and pair programming. However, over the years, in a false bid to deliver more, the leaders of these organisations have become less willing to allow product developers to practice some of these practices.

Vibe coding, which seems to be gaining a lot of traction recently, excites us, but for different reasons. As AI agents continue to feature as “team members” in product development teams, we would like to see product developers deploy AI Agents to code review, pair program, and write code using Test-Driven Development practices using patterns similar to Vibe Coding. This would ensure that as a team begins to churn out more code using Artificial Intelligence tools, the quality of the product continues to be upheld.

The promises are incredible, and this is an exciting time to work in the product development domain. We encourage our clients to remain adaptable and look for opportunities to experiment with these tools. Other areas that we believe AI would help include analytics, pattern detection in user feedback, generation of insights from application logs, and more.

 True agility isn’t just about moving fast - it’s about learning fast, adapting fast, and scaling what works. AI is not a silver bullet, but it is a force multiplier. For enterprise leaders, the challenge is deploying AI tools and embedding them in workflows that empower people, unlock creativity, and enable decentralised decision-making. By treating AI as a partner in agility, not just as a productivity hack, leaders can build organisations that are efficient, resilient, and responsive.