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Updated: Apr 24

Are you a CEO, CxO or entrepreneur amazed by Generative AI raw power yet struggling to visualise how to monetise its value for your business or venture?

We have completed value-focussed AI projects for several clients. Despite ranging across different industries, there are a few key insights and learnings that apply to all cases. Here you can read about them and consider how to incorporate them in your AI explorations!

An abstract image about language models and Gen AI


Here are a few, key learnings from our experience delivering AI POCs and MVPs for clients across several industries including media, analysis, recruitment and financial services:

1. Be very (very) clear what value you want to deliver from your investment, and develop measurable performance criteria to compare the ‘before’ (no Gen AI) and ‘after’ (Gen-AI assisted) scenarios. Review and improve these criteria continuously during your project. Design rigorous measurement and evaluation processes that provide actionable feedback to improve the solution during development.

2. Understand and model the human process. Generative AI projects in particular are often designed to augment or mimic an existing human process: identifying how an expert person would carry out the task can directly inform the design of a viable AI approach. Decide your level of ambition i.e. which tasks to be fully taken away and which to be assisted by the ‘co-pilot’ AI being developed?

3. Have the ambition to explore beyond automation! A Pluralit trained AI model can come up with interesting and unexpected analysis which can complement the judgement and experience of your team acting as a type of analyst co-pilot. And known risks such as hallucinations and accidental copyright infringements can be managed with the right partner like Pluralit.

4. Experiment, using AI experts such as Pluralit to select and implement appropriate AI technologies, initially as low-cost Proofs of Concept. Use rapid iteration, in an open and transparent process that engages people in your business with the AI team. This makes for enjoyable, joint learning and results that are ultimately trusted and adopted in the business.

5. Leverage (in the true sense) the value of your existing, unique data. At the very least, availability of data (such as the existing input and output of human processes) will help the AI team to identify patterns, develop and test approaches. At best, it may enable continuous machine learning where the AI itself is trained, and continues to learn based on your unique business knowledge.

6. It's never just about the tech. You need to pull other levers beyond AI to get value from your digital investment, including: change management, programme management, process engineering, testing expertise and agile innovation.

If you have a Gen AI application idea and would like to see how our AI and Data Solutions team can help to grow your business, let’s talk! We have developed the Pluralit AI Skills EngineTM, a reusable framework for rapid Gen AI value delivery.


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