• Colin Hayhurst

How to be an intelligent business

Updated: Jul 31, 2019



If you are reading this, you will most likely have adopted digital, and probably the cloud, into your business. If you hadn't, what would that have meant for your business?


What would not adopting AI into your business mean? It’s easily said that not doing so will seriously impact your competitiveness. What would be more helpful is to have some guidance on what can you do about it. In a series of posts, we'll aim to provide a practical guide for integrating AI into your business.


In this first post, I will discuss why AI is so essential for your business. In the next post, I’ll write about a strategy for adopting AI and aligning it with your business objectives. Then in subsequent posts, I will detail how you should approach AI adoption; how to consider the crucial aspect of preparing data for machine learning, options for how to resource projects and how machine learning can be developed and deployed.

Digital-first becomes AI-first



There is no doubt that the impact of AI on our society is already significant, and its importance will continue to grow. By now billions of us are using it; for email spam filtering, predictive text, voice assistants, news feed personalisation, product recommendations and so on. Anyone with a digitally native business should have thought about how it might impact their sector. Many businesses are talking about it. A minority, but a growing minority, have actually done something about it.


It’s my opinion shared by others, that every progressive business will, in time, be an intelligent business; in the same way that every progressive business is well down the road to becoming a digital business. Businesses that don’t recognise this are in real danger of falling behind, just as businesses that have not embraced digital (web, mobile, cloud) have done so. Consider companies that failed to innovate and suffered the consequences; remember Kodak, Blackberry and HMV?



Don't be fooled by the hype


Industries that are furthest forward in embracing AI adoption are, not surprisingly, also the ones that are the most digitised. Moreover, within any industry, the early adopters of AI are those that have already invested in digital capabilities, and notably cloud infrastructure. You cannot expect your company to successfully transform itself with respect to AI without first going through a digital transformation.


AI might be the most significant paradigm shift in technology history. One consequence of that is that there are many companies, notably startups seeking equity funding, that are making overblown claims for having AI where it doesn’t exist. In a detailed report on 2,830 EU startups classified as being AI companies, MMC ventures found that in 40% of cases there was no mention of evidence of AI; with the report author stating “companies that people assume and think are AI companies are probably not.”


My own experience of speaking with many businesses has confirmed similar findings. Some companies who claim to be integrating machine learning (usually stated as “AI”) into their products and services are not, in fact, doing so. Often such companies are just getting started, when you would think, reading their websites and blogs, that they are well advanced in having developed their machine learning capabilities and offerings. I have heard the same observation from other digital entrepreneurs and investors.


Transformation takes time


So why has this situation arisen, aside from the fact that some so-called AI startups are, or were, riding an investment hype cycle?


- Many businesses realise that AI will be transformative, so they feel the need to be talking about it, even if they are not doing it, yet


- It takes time to introduce and make effective use of machine learning in a business


- There is a gap between the demand for genuine AI talent and the supply of it


- Nowadays the tools and infrastructure exist for developing and deploying some type of machine learning model for the enthusiastic, if inexperienced, engineer. But, of course, developing a model that is effective in a real business is a different level of challenge.


Steps to becoming an intelligent business


So what can you do to genuinely and successfully adopt AI into your business? The steps to take in outline would be, I suggest:

1. Get (more) familiar with AI

2. Develop an AI strategy aligned with your business strategy

3. Identify a good (initial) project

4. Take steps to collect, clean and gather data; this is vital and can be the most significant challenge

5. Encourage and support your people: in self-learning, through training and hiring. Outsource or partner with external experts where appropriate.

6. Develop and deploy tools and models

7. Repeat steps 3 to 6


The next post focusses on business and AI strategy alignment. Later posts will discuss the topics in steps 4 to 7.


Fundamental to the successful execution of these steps is a commitment from the top, notably the CEO.


Are you ready for your journey to becoming an intelligent business?


#strategy #digitalfirst #ceo #innovation #aifirst

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