How Do Companies Identify AI Use Cases?

This insight covers the Fidra Analytics AI Journey, which is designed to de-risk your AI investment during Use Case development.

In terms of Gartner’s Hype Cycle, for some time now AI and ML have been steadily creeping from the depths of the ‘Trough of Disillusionment’ and up the ‘Slope of Enlightenment’. This transition is slow-going, but crucial for any tech to reach the ‘Plateau of Productivity’, where it begins to deliver the truly concrete business value. The inflated expectations finally cool into more realistic, achievable use cases.

At Fidra Analytics, we think this ‘cooling of expectations’ is absolutely necessary. It forces businesses to take several steps back, instead of rushing to implement unplanned or undefined AI systems. Ultimately, this will result in more successful AI implementation and less frustrated stakeholders, across the board.

It is easy to see how AI success stories pour from businesses who had embarked to solve a very specific problem. They took the necessary time during planning stages to figure out precisely what they wanted the AI system to smooth out. They ensured stakeholders knew what to expect, and how AI could deliver. It is these companies who are now reaping the benefit of their efforts.

What types of problems can AI solve?

Of course, those specific problems that successful AI implementors set out to solve do vary. Some may be entirely unique to one singular company.

Even so, the team at Fidra Analytics have pinpointed the Five Key Adoption Reasons most commonly spurring AI investment across all sectors:

• Enhancing Operational Efficiency – This was a problem Fidra Analytics tackled for tech distribution giant, Westcoast. We designed a RAG framework to aid the Presales team in lengthy information retrieval tasks. The AI powered solution has increased departmental capacity and loosened up the efficiency bottleneck. Complex customer inquiries can be answered much faster, relieving the previously overstretched team. Read our project case study for more details.
• Improving Customer Experience – Your Golf Travel was losing sales because of poor data management. Sales agents often had to end calls with customer questions unanswered, for finding the information within such a vast amount of unstructured data simply took too long. In the wait for a follow-up call, customer interest waned and revenue thus lost. Our AI solution structured all YGT data and made it searchable via a sales agent chatbot. This helps sales agents resolve customer queries and secure sales during that crucial first customer interaction. Read our project case study for more details.
• Driving Innovation and Competitive Advantage – BDO streamline day-to-day accounting tasks with their in-house AI solution, Personas. Employees, freed from more laborious tasks, have pivoted to providing more complex and strategic advice. Personas provides BDO with essential productivity and efficiency boosts that ensures they stay competitive in the market.
• Data-Driven Decision Making – Shell began using ML to predict valve failures way back in 2019. By analysing and utilising their machine data, they have hugely reduced unplanned downtime and saved millions of dollars. The system alerts technicians to problematic valves up to 75 days before they fail entirely and stop production.
• Compliance and Risk Management – As the Financial Times noted in 2024, the finance industry in particular has to fight fire with fire (or, fight AI cyber crime with AI cyber security). Mastercard deployed a Gen AI software last year that analyses all transactions, scanning 1tn data points to determine their authenticity. The tech promises up to a 300% increase in bank fraud detection rates.

From Drivers for Adoption to Use Cases

The Five Key Adoption Reasons highlight the importance of organised and thorough use case identification. To reap good ROI it is essential that businesses know their reason for AI implementation. Easy though it seems, discerning use cases is an exact science. “Throwing a bunch of AI at the wall to see what sticks” is a recipe for haemorrhaging investment and disturbing the CFO.

If you are struggling to research and discern the specific use cases that lead to the AI success stories of your industry, consider that businesses will not necessarily divulge their shiny new competitive edge. A good AI solution is like a ‘secret sauce’ for business – companies are unlikely to spread the specificities of their system predicted to generate huge operational and financial value.

We designed the Fidra Analytics AI Journey for this very reason, to bring our experience into your organisation.

Explaining the Fidra Analytics AI Journey

The Discovery Session allows us to engage in Use Case Identification with you. Focusing on your current data and operational problems, we can plan Use Cases and examine their feasibility.

This session sets a clear goal for Accelerator – steps 2 – 5 of the AI Journey, where we develop your POC or working prototype. Throughout the Accelerator, we work closely with our client in continuous test phases, adapting to feedback as it is given. We tailor the end result to fit perfectly and seamlessly within existing business ops.

Following the Accelerator, the project moves into Production. This is the stage of building, deploying, and scaling; where we turn the POC (prototype) into a working AI solution fit for company-wide use.

The Support stage comes last – we assist with product integration and resolve any further problems that arise.

The Fidra Analytics AI Journey allows for the deep understanding and dynamic thinking that drives our most successful case studies. We understand that visions and priorities evolve, as do project scopes. The AI Journey is designed to allow for breakouts, changes, and continuous refinement of the POC. Its structure naturally de-risks AI investment for businesses.

Working with Fidra unlocks the ‘art of the possible’

Get in touch to book your FREE OF CHARGE DISCOVERY session with one of our AI Solution Architects . Our focus is on finding the AI use cases that will generate the most business value for our clients. We even bring experimentation into the process (all under NDA) where we can bring some potential solutions to life before even putting your hand in the company’s pocket. If you have any questions or comments, please reach out to us, we would love to help! – info@fidra.ai

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