Think big, act small: the smart approach to adopting AI in your business
With so much hype around Artificial Intelligence at the moment, it’s tempting for firms to jump straight in and try the first AI opportunity that comes along. In fact, clients have been prone to ask me “We need AI in our business – how do we implement it?”, which is a bit like asking “Can we have an AI please?”. These are, of course, the wrong questions to ask. AI is a very powerful technology, but it is also a range of very different technologies, most of which are complex and can be tricky to understand.
So, for organisations thinking that they should be exploring AI but are not quite sure what it is or where to start, the simple approach that will save them money, time and effort is to ‘think big, act small’. Thinking big is all about developing an AI strategy that aligns with your business objectives and challenges, whilst acting small means testing out different approaches, and building meaningful proofs-of-concept that push the AI journey forward.
Importantly, this approach is relevant for small and medium-sized businesses as well as multinational corporations. Many executives believe that AI will cost millions and take years to implement, concluding that ‘AI is not for them’. But by understanding their AI ambitions (‘thinking big’) and how this journey can be navigated low-risk-step by low-risk-step (‘acting small’) the enormous value that AI can bring will be there for the taking.
And what sort of value will that be? Whether it is with ‘traditional’ AI or Generative AI, artificial intelligence will be able to augment the capabilities of the staff to give them better and deeper insights, helping them do their job better than ever, or provide enhanced levels of services to customers, or even completely new services. Large Language Models (with ChatGPT being the best-known) are a great example of how the Thing Big, Act Small philosophy can be put into action.
One of my clients is an analyst firm – they employ over 150 analysts across the globe to write insightful content on their particular market area. This content is offered to their customers via subscriptions to their portal – they currently have over 60,000 pieces of content available to subscribers. The first stage of the work we (GreenhouseAI and Bayezian) did with them was to develop an LLM Strategy: their AI ambitions were to be able to substantially enhance their offerings using Generative AI and, therefore, gain a significant competitive advantage over their competitors. In this case, ‘thinking big’ defined exactly where they wanted to get to. They could have wanted to completely transform their business using AI, or they might just have wanted to make some internal processes more efficient – all would have been equally valid, but now they had an approach that allowed them to identify the opportunities for AI that helped them reach their ambition. With some expert guidance, they were immediately able to produce a list of over 40 different opportunities for Generative AI, all of which were aligned with that ambition.
Then we moved on to ‘acting small’. Each of the opportunities was prioritised based on business value and ease of implementation. From the highest-ranked opportunities, we selected three different projects to build as proofs-of-concept. Each one was carefully defined in terms of scope to test specific aspects of the LLM approach. The first of these is an internally-focused application that creates summaries of assets using both internal data and web-curated data that is able to save the analysts many hours every week. The second is an application that provides summaries and translations of articles on the client portal – the customers are able to click on a button on each page to give them a ‘TL;DR’ version of the article and also a translation into Spanish or Mandarin (with other languages to follow). The third project, and probably the most ambitious and impactful, is a chatbot that is able to answer any question on the whole corpus of data. This gives their clients instant answers to any of their queries without them having to navigate the document hierarchy to find the right article to read. None of this firm’s competitors are offering anything like this capability to their customers right now. By building each small application they were able to offer leading-edge functionality very quickly and at low risk, thus stealing a march on the market.
Whilst the first application was relatively straightforward, it set the foundations for the rest to follow. Connecting to the appropriate LLMs and data sources, and then creating the vector indices of that data, can be one of the initial challenges with LLMs, but once set up this approach can be repeated for subsequent projects. Every small step is moving toward the firm’s defined AI ambition. And, from the prioritised list of opportunities, the client now has a pipeline of projects to build on: next on the list is an ‘In Case You Missed’ application that gives each customer a personalised summary of what has been published since they last logged on.
‘Think Big, Act Small’ provides the ideal framework to adopt AI successfully for the long term. The AI Strategy that is a product of that approach gives organisations an understanding of what the art of the possible is regarding AI and how it aligns to help deliver the business’s overall objectives.
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Usman Ikhlaq
Usman Ikhlaq
Usman joined techUK in January 2024 as Programme Manager for Artificial Intelligence.
His role is to help techUK members of all sizes and across all sectors to adopt AI at scale. This includes identifying the barriers to adoption, considering solutions and how best to maximise AI's potential.
Prior to joining techUK, Usman worked as a policy, government affairs and public affairs professional in the advertising sector. He has also worked in sales and marketing and FinTech.
Usman is a graduate of the London School of Economics and Political Science (MSc), BPP Law School (GDL and LLB) and Queen Mary University of London (BA).
When he isn’t working, Usman enjoys spending time with his family and friends. He also has a keen interest in running, reading and travelling.
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Authors
Andrew Burgess
Andrew is an AI strategist, ethicist, author and speaker with over 30 years’ experience. He advises organisations on their AI strategy, its application in business and its ethics. He is the author of ‘The Executive Guide to Artificial Intelligence’.
