Cracking the AI Adoption Paradox

My team specialise in co-creation with customers, focused on user-centric design principles, particularly in applied AI. We drive AI solutions from concepts into practical, business-aligned solutions through collaborative processes prioritising customer needs and strategic objectives.  

How does it work in practice?

Phase 1: Understand  

As a starter, to get to the innovation edge, we conduct a session  showcasing cutting-edge AI technologies through real-world use cases and live demos (show not tell) from previous engagements and R&D efforts.  

Then, by using what we call ‘Version 1 AI Jigsaw’ we uncover and prioritise use cases based on expected value and tech and data feasibility. This helps us focus on the most promising opportunities. Within one daywe can develop a high-level business case, outlining the expected value, technical complexity, and costs of priority use cases, ensuring efficient resource allocation. 

To ensure that the proposed solutions are desirable and user-centric, we employ design thinking methodologies. This collaborative process gathers user insights, aligns stakeholders and validates a solution vision. 

The outputs of this phase set the foundation for AI adoption by quickly identifying valuable opportunities and validating them with users, ensuring that solutions are both viable and impactful. 

Phase 2: Co-Create 

This is where things get exciting. With a co-created vision for the solution, our experts would then follow the 80/20 Pareto rule, designing a PoC to validate 80% of the vision with 20% of the effort: timeboxed within max 2 to 4, 1-week, ‘hypersprints’. This rapid phase involves shaping the design of a PoC that can validate the hypotheses co-created with your organisation. We present this ‘canvas’ before any development begins, including clear costs, deliverables, and success criteria.  

We then proceed with the Innovation ‘hypersprints’: one-week iterations with continuous client feedback to realise a solution that users can understand and try first-hand. This accelerated process is boosted by our internal IP accelerators, ensuring quick delivery of a real application that clients can play with and provide feedback on. 

The outputs of this phase include the PoC clear terms of reference, hypotheses statement, success criteria, and a custom MVP working application for users to access.

 Phase 3: Validate (& Next Steps) 

At this stage, users can interact with the application with no need for ‘change management’ or ‘upskilling’, as they have been part of its actual design and development, by being in close contact with the development team. We, in fact, co-created it. In parallel, we can construct an agile development roadmap, updating the business case based on lessons learned, and user feedback. This includes a plan for production readiness and scaling, providing more detailed information on revenues and costs.  

Outputs of this phase include the validated solution, an agile development roadmap, the updated business case, plan for production readiness and scaling: A quick, inexpensive, Golden Ticket – arguably the solution to PoC Lock, and Innovation Paradox. 

 Real-World Examples 

Our collaborative approach has significantly impacted various sectors, helping over 30 organisations kickstart AI adoption and solve both the innovation paradox and PoC lock in more than 20 cases, bringing to production solutions at scale. Notable examples include:

National Museum of Computing and Dyslexia Association: We developed web applications to enable live hyper-personalisation of content, catering to different audience needs. These tools translate and simplify complex information, making it more accessible and user-friendly, thereby enhancing educational outreach and engagement. 

Irish Public Sector Department: We designed a cutting-edge web app to automate the generation of functional and technical documentation, crucial for decoding legacy codebases. This innovation facilitates efficient, cost-effective application modernisation, significantly reducing the time and effort required for this critical process. 

Version 1 Internal Bid Assistant: To streamline our own processes, we created an internal bid assistant that summarises requirements and accesses historical intel quickly. This tool helps gather vast documentation, summarise requirements, and seamlessly access use cases and case studies, thereby accelerating our response to customer queries and improving the efficiency of our bid processes. 

An international company dedicated to sustainable development: We developed a domain-specific Virtual Assistant to provide rapid and reliable search capabilities across a vast repository of complex fire-safety regulation documentation. Designed with a human-centred approach, this assistant enables the customer’s professionals to access accurate, up-to-date information much more efficiently, empowering them to make informed decisions and deliver high-quality sustainable development solutions faster.

A Global Non-Profit: We created a live translator and simplificator for their website, enhancing accessibility by translating and personalising content based on audience age group and languages. This web app drastically improves the user experience, making complex information more understandable and accessible at a sustainable cost.  

These examples illustrate how our co-creation approach delivers tangible benefits, solving real-world problems and driving AI adoption from proof-of-concept to production, at scale.