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AI represents an existential threat for large organisations

Artificial Intelligence represents the biggest existential threat to traditional organisations that we have seen in decades, but not for the reasons that one might expect.


AI will undoubtedly change the way we live. Whether it be proactive virtual assistants with predictive smarts, true automation of tasks that are not simply repetitive but need complex decisions, or any of the plethora of future use cases that lie beyond popular comprehension, the AI revolution is upon us. And yet these modern wonders are not what could spell the end for today’s biggest institutions.


The competitive differentiator for incumbent organisations will be their ability to rapidly scale AI and commercialise the many opportunities it will represent. As per this excellent article in the HBR, technology will not be the source of advantage, especially when the underlying capabilities that power AI will be subsumed within a few large and global platforms. There are in fact quite a few similarities between the tantalising promise that data represents to most organisations and the commercial tease of AI. I say ‘tease’ not because the opportunity is ethereal, but rather because the very real benefits are likely going to prove hard for most incumbents to access.


Most large organisations now have a dedicated focus on data. Across every industry, the opportunity for data capabilities to unlock value is well understood. However, how many large incumbents have truly unlocked game changing value by leveraging data? Data lakes are not new. The technology is not the barrier. Rather, the ability for organisations to change their operating models, culture, leadership mindsets, attract the right talent and ultimately evolve their business model to take advantage of data are the limiting factors. Why will it be any different for AI? Many of our clients are already experimenting with AI, and so they should. However, the path from pilots to at scale commercialisation is not so clear. In essence, deriving game changing benefit from AI will require incumbents to solve the exact same challenges that have to now inhibited their ability to capture value from data.


There are two additional nuances surrounding AI that are perhaps not as relevant to data; nuances that could be so fundamentally important to threaten the very existence of incumbents in a way that the lack of data commercialisation has not. First, AI impacts relationships between humans to humans in a way that data does not. Second, AI is impacting organisations at both the supply and demand end of the equation simultaneously. This second differentiator is perhaps not so obvious. Data changes an organisation’s ability to derive insights, take meaningful actions, target the right customer, optimise supply chains, along with having many other potential benefits. These opportunities however are mainly internally driven (I am referring to this as the supply side). The fact that a bank or tech giant knows me inside and out, my spending habits, my preferences, which side of the bed I sleep on… hasn’t completely changed my life. My behaviour, patterns and ways of thinking remain the same and I expect organisations to adapt around me based on their new capabilities. On the other hand, the potential for AI to change the way consumers live their lives (I am referring to this as the demand side) is far more potent. Whether it be home robots, autonomous vehicles, AI driven financial planning, predictive health, energy optimisation or whatever else our imaginations can conjure up, the impacts of AI will likely see me adapting to the technology. AI will change the game both internally within organisations and externally across a social context that surrounds the organisation.


This nature of AI and the magnitude of change it represents means that corporate disruption is inevitable. The cynic will ask how this is different to any other time this century. The answer may well lie somewhere within the above two nuances.


What does all this mean for the incumbent organisation who is geared towards cost efficiencies and incremental growth but not towards embracing step change disruption? I believe that the imperative to adapt internally to embrace the opportunities and threats represented by AI has never been more pressing.

That is why I am so passionate about our much broader approach to growth that we call Growth Orienteering. Maybe our corporate leaders will get better at growth when it is no longer a nice to have but a matter of survival. By way of example, if a retailer was slow to build single customer level data visibility and find ways to better target as a result (and many are still not even close to being there), it meant a lost opportunity, potentially a tiny bit of market share loss if competitors had their acts together, but it certainly hasn’t been seen as an existential threat. Will the same be true for tardiness in adapting when it comes to changing the way humans interact with each other or with services that have been heavily people dependent such as financial services, health services or professional services (legal, consulting, design)? Could the very absence of human intervention in certain B2B industries challenge governance and operating models to the point of breaking?


If I was sitting on the Board of a large incumbent, I would be very scared right now. Not because of the technology, but rather because my organisation has probably shown a level of ineptitude when it comes to extracting value from data which in turn gives me very little confidence that it will be positioned to survive let alone thrive within the AI tsunami that is upon us. I would want to see a heap of AI experiments blossoming across the organisation. This doesn’t mean leading the charge in building AI models or driving the tech. I would be looking for a portfolio of experiments around how existing AI tools can generate efficiencies or growth potential. Then, and perhaps even more importantly, I would be interrogating senior management about what they are doing to adopt a new operating model to allow them to scale the AI experiments that do work. 


I will leave you with this thought. I recently did a keynote speech on the business landscape in 2050, and there were plenty of eye rolls as I spoke about AI. Yet. in the age of the horse and carriage, the automobile was inconceivable to the wise heads of the day. 30 years ago, the idea that we would carry around portable communication devices with the computing power greater than a supercomputer of the time would have been laughed at by most corporate leaders. A mere 3 years ago, the explosion of AI was beyond the comprehension of most executives. History tells us that AI is going to be big, so woe to the senior executive team that doesn’t hasten and take decisive action to internally prepare their organisations for what is about to come.


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