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With Digital Transformation going at a pace, Prof. Niall McKeown discusses the role of the business leader when it comes to building a business that can create a new, sustainable competitive advantage, leveraging artificial intelligence.
Okay, if you don’t mind, I’ll switch to English. My Finnish is a little rusty, so I was never a strong Finnish speaker. My name is Niall and I come from Northern Ireland. Northern Ireland is part of the United Kingdom. We voted to remain in the EU. The mess that is ensuing is not our fault and is particularly not the fault of my small region of where I come from in the UK.
I’m here to ask the question (and hopefully answer it) is: “Will AI make you irrelevant?”
I started my business 20 years ago. June, actually, in 1999. Of course, I was seven years old. You can tell to look at me! And when we started, we created one of the first high-capacity email broadcast engines. We wrote every line of code we put it on servers and we put it into the hardware infrastructure inside major banks and corporations around the world.
Business grew rapidly and we thought everything was good. We were safe, secure. That was until 2007. Someone came up with an alternative version. It was pure quality. It wasn’t as fast. It sat in the cloud, whatever this was. I remember in 1999 this is five, six years before the invention of YouTube, several years before social media. And we progressed thinking that life would continue on that trajectory forever.
But the introduction of cloud, and the movement of email marketing to marketers and away from technologists, caused a disruption in our marketplace. We shrank dramatically down to a mere 7 staff, having grown year after year. We thought our clients (which included Wall Street banks, the European Bank, Reuters media agency) they would never leave us.
Within 16 months they all did. When disruption happens, it happens fast and I wasn’t prepared for it. That’s what took me into academia to try to understand how this phenomenon could happen. And it’s not a new phenomenon. Disruption is not new: ask the candlestick maker, ask the person who shoes the horses, the blacksmith.
This is my hometown in the 1930s. All of these ladies are at a conference about electricity, an electricity conference. It seems a little crazy. Electricity: it’s ubiquitous. It’s everywhere. Back in the 30s, electricity typically had an electricity strategy within a business. There was someone in charge of electricity. My argument is that there’s no difference between the electricity of the 1930s and the digital technologies of today.
We’re at a conference to find out what it’s going to be like, some predictions, but the answer is the same as electricity: it is ubiquitous, it is a low cost, it is everywhere. Having access to it does not make a differentiated business. Having access to it is not going to create a competitive advantage, that’s why we stopped creating strategies around electricity.
But yet strangely, we create strategies around digital, as if there’s a digital strategy as if that’s going to make the differentiation. It’s not. It’s people that will make the differentiation. It’s what we decide to do with these tools that’s going to make the differentiation. And like electricity disrupted industries, the new technology of AI is going to radically disrupt and change industries.
The story of AI is a long-winded fairy tale that goes right back to the 1950s. This isn’t new, electricity was in Ireland in 1880. It didn’t really come into play until the 1930s. AI has been around since the 1950s when this gentleman, John McCarthy, (of Irish descent I may say, definitely Ireland is going to claim it invented AI, just give us a moment and we’ll do that!) McCarthy coined the phrase “artificial intelligence”. It was the idea of being able to simulate human cognitive behaviours through computing means.
AI then started to get its bumpy take off in the 1980s, and this was around the invention and turn of email. Email was either authentic or spam and it was impossible to write computer code that could really detect the differences between it. But if we could create a machine that could learn, then the machine could perhaps identify as the environment changes and new types of artificial or of new types of emails and spam emails are coming in. This was the first time we really started to see this cognitive behaviour, this learning behaviour, starting to grow.
So, AI then became “machine learning”, a subset of AI. The machine could learn. It required volumes of data. Data is the fuel for AI. Move forward to the 2010s and we started to see deep learning. Deep learning is when you combine the volumes of data with the might of mass networked computing, cloud computing, starts to come of age.
So when you’re hearing these terms, “AI”, “machine learning” and “deep learning”, deep learning is a subset of machine learning, machine learning is a subset of artificial intelligence and John McCarthy is a subset of Ireland.
So why is this different to what has gone before? It’s different to what has gone before, because before we had to program the computer to do stuff. We had to map out the decision trees. The decision trees would then be executed through some form of a technological breakthrough. But now the decision tree doesn’t work like that. Give me data of the before state, give me data as to the end state and like this jug, you pour in the data and the computer will learn the best way to get from point A to point B.
And that does not matter if you’re in medicine and you’re doing triage as a doctor, or if you’re in finance and you’re trying to conduct better sequences and methods for delivery in finance. Finance is principally decision tree driven and when it’s also heavy with data and when you see data and decision trees, it’s the perfect combination to automate and optimize with AI.
And AI is on the exponential growth and rise. We didn’t hear of AI in the 50s. We didn’t even hear about it in the 80s and that’s because with exponential growth, it can quite often go below the radar. Exponential works like this: if you had one step then you take two steps, then it’s the size is four, then 16 and then 16 times 16, it grows and that curve like that bacteria is growing.
We are on this point where it’s starting to break through. It’s starting to get acceptance and this is how technology growth curves are working. This isn’t some new phenomenon. If the growth was 0.01, then the next step is 0.02, 0.04, 0.16, all unnoticeable. But the moment it breaks through, it becomes noticeable. If you were to take one step and it’s to grow exponentially, by the step 30, it will have gone 1 billion meters, that’s 27 times right planet Earth for your 30th step!
We’re not too far off hitting exponential, yet how many strategies have planned for this? How many CFOs are sitting down, going: “in the next two to three years, we’re going to see an exponential rise in artificial intelligence which will automate practically everything we can do, let’s stick that into the strategic plan”. It doesn’t happen like that.
We think linearly. Except for those that are the digital innovators. We’re even seeing large banks and institutions saying that it’s time for management to think beyond the process of innovation and also consider alternative budgeting approaches for capital structures that fuel critical work surrounding AI.
So, what we’re now saying is even innovation isn’t enough in and of itself. It’s innovation and optimization must go hand in hand. Auditing is going to fall to AI. It’s already starting to happen in large institutions. Banking is radically changing. Risk management, investments, all of this is starting to be optimized through AI. Credit, Capital, I’m only on the letter C and I could have taken automotive as my “a”.
I could take any industry that has a decision tree in how it works and data at the start and an outcome at the end and I could pour it in and I could write a completely different list. It’s all leading to one thing: disruption. Disruption of our roles, of our jobs and how we conduct ourselves and what we’re going to do when we get up in the morning.
So you’ve two choices: either by in AI, let it happen, let it slowly erode and take over roles and posts (which I’m not criticizing, just be aware that that’s the choice) or we can leverage the data that we have and start to innovate and utilize this new technology and lead that change as Chiefs of Finance. And the role of Finance, as we will see, is one of leadership and one of giving direction and one of purpose.
My experience is that the technologists don’t let you down, it’s the leaders that let you down. My experience is that if you can think it, they can do it. If you want it done, the technologists typically deliver. Now, what was it you were wanting them to do? And in the absence of leadership, the best they can do is digitize what they have. A pilot does not need to understand thermodynamics to fly the plane, to take off and land safely.
She doesn’t need to understand how the engine works, how it super heats air and pumps it at the back, that’s not what’s required and a CFO does not need to understand how the technology works, but they do need to understand its business capabilities and they do need to give direction as to where the business is going. As a member of the board, if we are chief of Finance, we must give directions, not the technologists. They cannot be doing this on their own. It’s a requirement of the entire leadership function of the business.
The problem that we’re seeing is that quite often its technological “pull”, what can the technology can inspire us to do and not so much of the strategy “push”. In the absence of this, we stall at phase one of transformation, which is to digitize the existing business. We digitize it and go “Phew! Dodged that bullet!”. In reality, we need to digitize, yes, but then we need to transform.
What is our new unique value proposition in the digital economy? Because the one we had in the traditional economy doesn’t float well in the new digital one. And how do we restructure our businesses to make that happen? And then how do we optimize enabled by AI to make that happen? And the gap that’s typically missing is leaders able to control and manage innovation, the subject matter experts.
So is AI (if a took your role) a bad thing? Not if you’re going down the road of innovation. Eric Hoffer wrote (he’s an American author and psychologist) he wrote:
“In times of great change (which is always), learner’s inherit the earth while the learned find themselves beautifully equipped for a world that no longer exists.”
Your upgrade to your thinking is in your control, it’s in your choices, it’s in your hands. Understanding AI and the technologies and its capabilities is something that you must understand as business people. It is not going to be like an upgrade that happened before, this is not going to be this same.
True innovators don’t actually really talk that much about the technology. They start off with the customer problem or unmet need. They focus their innovations and resources to ensure that they deliver maximum value to the customer. They’re using data to test hypotheses. As finance people, we tend to use historic data. As innovators, we tend to use predictive data. The best people to help bridge this data gap is actually those who are most adept at data, which is typically finance.
In the absence of doing convergent innovation, where we have defined the exact point in the digital economy we would like to be in, where we’d like to play, we then switch to “divergent”. Divergent is where we hand the keys of the business to the technologists without direction and this is not the fault of the technologists. They then look at the technology that’s available to them and they start to build solutions. Then they look for the problem, “oh, we could optimize this”. This is why they’re going to perpetual phase one digitization, not true transformation.
And our fieldwork has shown us that this is happening across the globe in large/ small/ medium enterprises. It’s not a unique thing, it’s not a thing around an industry, it’s around a profession. It’s leaders, particularly CEO/ COO/ CFO. They don’t give adequate direction. Divergent innovation takes hold, because they demand innovation, but not to any destination, resources get squandered, people lose faith, disruption happens.
There are three types of innovation: closed, collaborative and open.
“Closed” is where we think we have all the answers. We do it in-house. Every industry has squeezed the juice out of that lemon. It’s not where problems are found or innovations are found anymore. The innovations are found collaborating with new partners, adding new datasets to our AI along with our own, being able to find new problems that wouldn’t exist in our industry specifically alone.
“Collaborative” innovation where were cooperating with others, co-creation is the new hot spot for innovation, but that does not make it easy, because I can say it. Apple’s latest product is a credit card product. Did Apple create it? Yes, co-created it (sorry) with Goldman Sachs and with MasterCard. The world’s wealthiest company sought to partner. It’s not a lack of resources, it’s wisdom.
So do we have the wisdom to do the same? Here’s the major problem: in traditional financial business modelling, the business that we produce/we sell/deliver products and services, and at the bottom is where we create the value, we do it internally. How do we get the idea from the bottom of the business to customers at the top?
Well typically, we build business cases. Typically we test the market internally and we do that. And actually it’s quite easy to do when the technology is reducing the operating costs and creating efficiencies, that’s easy. But transformation doesn’t happen there. Transformation typically happens further up the scale. New products and services, innovations co-created. That is not a comfortable place. In fact, it’s very uncomfortable.
“Because I need some money, CFO”.
“To do what?”
“To work with three partners.”
“What’s their balance sheet like?”
“Not particularly good.”
“Oh really? How much do you need?”
“As yet undefined.”
“What is the outcome?”
“Not quite sure yet, but we know magic will happen once you fund it… Can I have some money, please?!”
Who’s going to pass that as a business case? Of course, I’m being extreme, but it’s definitely a much more difficult risk to be managed inside of the business. Belfast did electrify. Belfast grew and prospered. We are still going to be existing, we are still going to have our jobs at the end of whatever it is that we do. We will modernize and we can go with the flow.
But I’m going to end by answering the question that I started with, which is “Will AI make us irrelevant?” My answer is no it won’t, if we deliberately engage in upgrading our own understanding of what’s happening in this groundbreaking new technology that is equivalent to the electrifying of our organisations. It is on that scale and if we choose to leverage it, rather than have it applied to us, we will by no means become irrelevant. We will become the superstars because what is missing is subject matter expertise such as yours in order to be applied to innovation.
Thank you very much.
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