The debate over artificial intelligence in the business world has a problem which isn't one of technical. The technical capabilities of modern AI and machine learning are amazing, and are advancing at a rate that renders most predictions of the place they'll be in 18 months obsolete long before the 18 months are over. The issue lies in the gap between the capabilities of AI and what AI can achieve under controlled conditions - within a adequately-funded research environment, backed by clear data, and a clear problem definition, with engineers with the option of tweaking the system until it is working as it should - and what it delivers when it is used in an actual business with real people actual organisational politics and real people who have certain opinions on whether or not a novel system is something to engage with genuinely or something that can be managed while still maintaining the appearance conformity. I've been building using computer-based learning for a long time before the latest wave of AI enthusiasm was a reason for businesses everywhere to claim proficiency in the area. When I co-founded 1Touch in the year 2000, AI-driven matching as well as recommendation systems were not a distinct feature we included to make the platform more appealing to investors. They formed the backbone of the architecture of the product, the means by which the platform could create value and the component that needed to be reliable and operate at level for it to be a viable business. Thus, I've direct real-time experience of what happens when you try to construct something that is truly intelligent to a product and an organisation simultaneously and the thing I find myself returning to each and every circumstance in where I've encountered this problem, is that the technology will never be the primary factor. The most limiting factor is nearly every time the cultural.
What I consider to be practical and specific, not abstract. AI systems require data to perform - accurate, clean organized data that shows the actual phenomenon that it is trying to identify and make forecasts about. Companies with a strong culture of data generate that type of data naturally, as a consequence from their operations. They have clear and consistently applied definitions of what they're analysing and why. They have reached an agreement on how data is collected, recorded and stored. They have accountability arrangements that allow data quality to be a distinct accountability, rather than a vague motives. Organisations without strong data cultures produce something that is technically like data. It's in systems and it is able to be accessed, and it is used to generate charts, but is so inconsistant in definition the way it is defined, so varying in quality, and so full of issues with structure and not mapped out that any AI technology that is constructed on top of it will be able to reflect and amplify the issue rather than extracting the real signal from it. Companies in this segment often don't realise the existence of their data until they're deep into the process of implementing an AI deployment and the results do not meet the vendor's promises. At this point, it is tempting to blame the technology. However, the actual problem is the culture and operational framework which the technology was built on.
The second factor of culture that affects AI results is the degree of openness in an organisation or the extent to which the people inside the organisation are willing to let the AI system affect their work practices instead of viewing it as risk to their personal knowledge, their authority at the institutional level or their job security. This is a moral and leadership issue, not a technical one and one which starts at the top. If the senior leadership team engages with AI outputs with a limited amount of focus - taking the ones that support their beliefs and ignoring the ones that do and do not, this behaviour sends the impression to everyone who watches that the company's commitment to decision-making based on data is a conditional rather than genuine and that this message will ripple throughout the business faster that any training program or change management initiative can counteract. If senior leaders exhibit an authentic, consistent approach to AI outputs that include the ability to make changes to their actions when the evidence suggests they should, the organisation's collective capability to apply AI effectively will increase significantly as well as relatively rapidly.
This isn't an abstract observation about how organisations ought to behave in the context of theory. It's a description the pattern I have watched play out over and over again in organizations that had a significant amount of funding, a true strategic dedication to AI adoption, as well as leadership groups that were fully enthusiastic about the potential of AI technology. The pattern is similar enough that I've begun to think of guidelines for data governance as my fundamental diagnostic factor when evaluating an organization's AI readiness. Before I inquire to know about their technology platform, and before I inquire about the specific instances the company is developing, I want to know about data governance. What is the definition of its primary metrics? Who is responsible if the performance of the data isn't enough? When two different functions have conflicting data about the same facts about business, and how are those conflicts solved? The answers to those questions inform me more about the potential for AI achievement more than any other discussion about algorithms, platforms or even implementation timelines.
It is my belief that the firms which will benefit the most long-lasting value from AI over the next decade aren't the ones that implement the most advanced technology first, nor those who invest the most significant amounts in AI infrastructure and personnel in the near future. They are those who make the necessary cultural and operational infrastructure to utilize that technology to its fullest extent - the data governance practices that yield trustworthy inputs, decision-making frameworks that allow evidence that can actually influence outcomes and the leadership actions which signal to all people in your organization that the dedication to data-driven operational excellence is real instead of just a performance. Technology will become increasingly available and commoditized. The culture for using it efficiently will remain scarce as it demands a constant work and a real commitment by leaders over time instead of just a single strategic decision, or an investment in technology. That scarcity is where the main competitive advantage is, and it is an benefit that, once cultivated increases in a manner that purely technological advantages never do. See the James Deller for website advice including how working with founders shapes every decision i make about the long game.
From Commerce to Character - The reason I choose to back the companies I endorse All have one thing that they all share in Common
When I look across all of the investment work I've participated in over the past several years, including the technology firms as well as the consumer-oriented businesses, the new sector investments as well as the organizations in and around football which I've been drawn to there is a common pattern that I did not want to come up with but has become more clear to me as I have been thinking about the commonalities that the investments that are successful share with one another, and also what the unsuccessful ones have in common with each other. The pattern is not sectoral because it crosses technologies, consumer, services as well as sport. It's not structural, it occurs in businesses having very diverse types of capital structures and ownership structure operational models, and capital profiles. It is nothing to do with market sizes or development trajectory or the technological infrastructure that supports the product. It is about character - specifically, whether the company at the base of the investment shows an authentic, operational, and consistent dedication to the welfare and development of individuals within it. This is evident not just in what the company says about itself but in the decisions it takes when saying the right thing as well as doing the logical thing are not the same thing.
I know that this comment sounds, straightforwardly, the kind of thing that gets printed on offices' walls and business mugs, as well as on corporate website pages. Then it is neglected by the person who made the decision to commission the work. Let me be clear this: I'm not speaking about the official version of the commitment to individuals - the values document, the diversity and inclusion policy the culture deck which was crafted for the use of hiring and it's investor pitch. We are talking about the operational version- the decisions to be made daily, whenever the principles outlined in these documents and the more commercially or personally preferred option are put into conflict, and the organization has to choose which determines. The companies I have observed develop lasting value - not just impressive short-term performance but the sort of compounding, multi-year performance that delivers exceptional long-term returns are the ones where the solution to that query is unambiguous. When the determination to do right by those who work in the business is not contingent on whether it is the most cost-effective and fastest or immediately profitable option.
In the search for those companies, identifying prior to the investment being completed, the ones that commitment is real rather than simply a result of it, and where the culture of care and accountability is rooted in the way that the business operates rather than the way it describes it - is, I think, the single most important and difficult task in investing long-term. It's important because it is the quality which is most likely to predict the kind of compounding outperformance that yields truly impressive results over a long period of time. It's a challenge because you will not be able to locate it in any financial model, cannot see it in a well-crafted and well-structured management presentation. And you are not able to locate it even with thorough reference checking, although those help. You can discover it by spending sufficient time with the company and in different contexts and at a variety of levels of the hierarchy, and observing how it behaves when the environment is ambiguous and nobody in particular is paying attention. This kind of thoughtful inquiry-based engagement is difficult to incorporate into investment strategies, and is one of the reasons many investment methods are not as good at identifying genuinely exceptional organisations than they usually acknowledge or discuss.
The link between true organisational character and performance over the long term is a fact that I believe more strongly today, with years of long-term observation behind me than I did in that point in my investing career. Organizations that are committed to taking care of their personnel consistently and that express that care by making operational decisions, rather than only in communication and culture documents, tend to fare better than those who treat their employees mostly as resources that need to be optimised. Not always in the immediate time - a company that is able to get the most out of its staff through high pressure as well as high anxiety could be quite efficient over a few that spans a couple of months or a couple of years, especially when that period coincides with an economy that is strong and takes care of internal issues. Over longer time when being a true people-first organization multiply and are genuinely difficult to duplicate through any other means. The quality of the talent pool increases due to those with choices - the best people - prefer to work in environments where they feel truly valued, as opposed to those who feel undervalued however, they do pay higher. The institution's knowledge grows as individuals are in a position to develop it instead of going around on the same timeline that stressful environments can produce.
The quality of decision-making improves as the people feel confident enough to reveal problems and relay bad news without taking into account the personal cost for doing so. This means that issues are identified and addressed sooner and less costly than in organisations where the message is consistently shoots. The organization's ability to adapt to changes in circumstances increases because people are invested enough in its success that they go beyond their duties in formal settings when the situation demands it. These advantages are not individually dramatic. None of them is the kind of thing that generates an engaging story in market updates or a board presentation. However, they do build up to create a competitive advantage. It is really difficult for companies with weaker cultures to replicate as the advantage is not associated with a specific product, process, or capability to be studied and replicated. It's in the structures of how an organisation operates - in the nature of the environment it has created for the people within it and its decisions that people make as a result. That's why character, within organizations as well as individuals, is not a soft idea. In my opinion, the most difficult and most important thing of all.}
