Recently, I grabbed a to-go coffee between meetings. As the coffee arrived, I tapped and left. It felt light, given the size of the cup. I lifted the lid and stared into the foamy abyss. Using the wooden stirring stick as a dipstick, I realised my large coffee was 70% foam!
It’s much like the current hype about AI.
If the job of a coffee is to have the caffeine keep you racy, pacy and alert, why the big cup if it is 70% foam? We buy with our eyes, and the psychological economics of different cup sizes and price points makes for smart retailing.
The same triggers in our brain that let us buy with our eyes activate around the AI hype feeding hope and fear. And the world of AI did a great job of it with the introduction of ChatGPT earlier this year. And that is where it feels like it has stayed.
In response to the impact of ChatGPT, we sprang into action and spoke to our teams. The message was clear. You’re fired if you ever approach me with a question that ChatGPT could answer. However, if you ever come forward with an answer that ChatGPT provided and that you could not explain or argue, you’re equally fired. Two juxtaposed positions are dramatised for impact but point to a simple, clear message. Get with it on tech, or you are no longer relevant in the world of future commerce, and that future is now.
Mindset matters, and adopting the right one to technology is essential to stay relevant and solvent. But mindset on tech is not enough to use it effectively and profitably.
Over the last 6 months since ChatGPT sprung into the market, we’ve reviewed multiple AI solutions or strategies proposed by clients across most industries. By far, most have been theoretical in value or moribund in reality. I write from the position of established mid-sized businesses with annual revenues between £5m-£75m.
Theoretical in value
Be it the hype, noise and thousands of AI hack infographics on LinkedIn; videos on YouTube and articles in the digisphere, the world of possibility is interesting but not practical. From taking jobs, doing jobs, and creating new jobs, what started fast has slowed as quickly. Bringing real productivity gains into your business without losing a distinctive personality remains a hope and dream rather than an accessible, practical reality. Building AI is hard and expensive, monetising it across a broad landscape through SaaS offerings and overcrowded app stores is harder.
Moribund in reality
Already, ChatGPT feels like it’s entering this categorisation. Has it become dumber? The quality of answers it offers on mostly similar questions I asked over the last 6 months has waned. It has left me wondering if a suite of privacy interventions has compromised its ability to generate more meaningful and robust answers. Even prompt engineering hardly distinguishes one answer from the next. Across marketing, content generation seems to have peaked already, with little or no impact on the cost and investment in time and money to use the ocean of AI options.
A profitable reality
Across more than 3,000 companies, we see an approach, rather than a neat AI app, win the day on digitisation and AI solutions. However, it’s not about a hack or infographic on bringing AI into your business profitably. Like most successful acts in business, it goes down to the basic principles of what informs your action in building your business and step-by-step patient work.
First, know what business you are in. It has nothing to do with your product or service whose sole job is to solve a problem for your customer. It is all about who that customer is. Broad definitions of customers harm your ability to get this crisp and clear. Narrow definitions of customer are notoriously hard to get right. Yet, they are the blueprint against which your business should be defined, built and shaped.
Second, articulate your commercial activities, processes and procedures using this blueprint. How they are designed and implemented must be determined by that blueprint. The smart way to do this is with your team. Their involvement will create ownership and accountability as well as measured outcomes.
Finally, these activities hold the key to digitisation and AI adoption. Whether across marketing, sales, fulfilment, administration or procurement, inefficiencies and dull processing requirements are the first areas that lend to digitisation. Try it with your functional teams. Ask what is the most tedious part of their job and start there. Take that activity and see how it can be digitised using off-the-shelf or native software.
Don’t put the horse before the cart.
What is critical in this process is that you start at the beginning and define your business. For example, adopting software to digitise a marketing or sales process not designed and characterised by your customer segment’s behaviour creates a generic experience. Perhaps we no longer respond to canned marketing emails or automated sales engagements. If you start with the software, you will build what everyone else already has because they use software to create structure and systems, not the lived experience of the people in the organisations that engage and buy answers to problems.
AI is exciting. We have baked it into our platform across 3 areas. It’s working okay. Each week, it gets better as we learn its limitations and potential. Adopting technology is a vital act of leadership. Leading it, adapting it and recognising that it does not hold all the answers but will hold many opportunities is a critical mindset.
