Why Years of Investing Changed What I Look For About Lasting Impact

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AI Can Only Be As Effective As The Environment It's Based On
The debate over artificial intelligence within the workplace is fraught with problems and the cause isn't a technical one. Modern technology and capabilities for AI and machine learning platforms are astounding, and they are growing rapidly, making most predictions on how they will perform in about 18 months obsolete well before the 18 months are over. The problem is the gap between what AI can achieve under well-controlled conditions - in a adequately-funded research environment, backed by crystal clear data, a clear definition of the issue, and engineers with the option in experimenting until their system does what it is supposed to do - and what it will actually do when implemented in real organizations with real cultures actual organisational politics and real people who have their own established views on the quality of a system. something to engage with genuinely or something that needs to be negotiated while still appearing to be in compliance. I've been developing with computer-based learning for a long time before the latest wave of AI enthusiasm created a trend that everyone in the business world boast of their expertise in the field. When I founded 1Touch with my partner, AI-driven matches and recommendation systems were not an additional feature that we incorporated to make the platform more attractive to investors. They were at the heart structure of the product's architecture. They were an element that made the platform was able to create value and also the element that needed to be reliable and operate at scale in order for the business's viability. That's why I've had direct in-person experience of the things that happen as you try to implement an intelligent system and a company simultaneously and one of the lessons I always come back to throughout every situation in the past I've faced this kind of challenge, is that the technology is almost never the only factor that is limiting. The limiting factor is almost entirely the organization's culture.
What I am referring to is particular and practical rather than abstract. AI systems need data to work - consistent, clean properly-structured data which captures the thing that the system is trying to analyze and make predictions about. People with strong data-driven cultures create that kind of data naturally, as a result of how they function. They have clear and consistently applied definitions of what they are measuring and why. They have agreed on conventions for how data is recorded, collected, and stored. They have accountability structures that make data quality a clear task rather than the general intent. Organisations without strong data cultures produce something that technically looks like data. It's there in systems and can be accessed or used to produce charts, but is so inconsistent in definition and so variable in its quality, and so full of issues with structure and not mapped out that any AI technology that is constructed on top of it will reflect and amplify the underlying mess instead of drawing a real signal from it. The organisations in that latter category tend to not realize their existence until they're well into an AI deployment and the results are not matching the vendor's promises. At this point, it is tempting to blame the technology. most of the issue lies with the cultural and operational infrastructure which the technology was based on.

Another dimension of culture that determines AI results is the degree of openness in an organisation as measured by the degree to which those working within the organisation are genuinely willing to let an artificial intelligence system shape the way they operate rather than focusing on it as risk to their personal skills, their authority within the institution, or their job security. It is a societal and leadership problem but not one that can be solved by technology that needs to be addressed. It is a problem that begins at the highest level. If senior executives engage in AI outputs in a way that is selective - accepting the results that reinforce the previous beliefs and ignore those that are or do not – this sends that to others that the company's commitment to a data-driven approach to decision-making is a conditional instead of genuine, and that conditionality will propagate throughout the organization faster than any formal training program or change management initiative can stop. If leaders show an ongoing, consistent commitment to AI outputs, including the ability to modify their actions when the evidence suggests they should, the collective capability to apply AI effectively is significantly improved and quite quickly.

This isn't an abstract statement about what organisations should do in theory. This is a description the pattern I've observed play out repeatedly in organisations which had significant financial resources, a real strategic commitment to AI adoption, and senior management teams that were enthusiastic about the possibilities of AI technology. The pattern is similar enough that I've decided to treat data governance practices as a key diagnostic point when I am evaluating any company's AI readyness. Before I inquire concerning the technological stack before I ask questions about the specific application cases the organisation is exploring, I inquire about data governance. How does the organisation define its primary metrics? Who is responsible when the quality of the data isn't high enough? Does it matter if two different groups have contradicting data about the same situation in business and how are these conflicts solved? The answers to these questions provide me with more information about the chances of AI performance more than any other discussion regarding algorithms, platforms or implementation timelines.

I believe that those businesses that will get the most durable value from AI in the coming decade will not be those who adopt the most advanced technology first, or the ones that invest significantly in AI capacity and infrastructure in the near term. They are the ones that build the cultural and operational foundations for using that technology in a productive manner - data governance processes that provide high-quality inputs, the process frameworks that enable evidence-based decisions that truly impact outcomes in the long run, and the behaviors of leadership that let everyone know in the organization that the commitment towards a data-driven process is real instead of merely a matter of performance. The technology itself will be becoming more readily available and less expensive. However, the culture that can use it efficiently will remain scarce because it requires constant dedication and effort from people in leadership for a long time rather than an individual strategic decision or an investment in technology. This is where the true competitive advantage lies, and it is an advantage that, when built can be built upon in a way it is not something that just technological benefits ever. View James Deller for blog advice including how scaling tech companies changed what i look for about teams.



From Commerce to Character- Why the Businesses I Back All share one thing in Common
When I look across the spectrum of investment work I've participated with over the last few years – the technology-related businesses along with the consumer business, the investment opportunities in the emerging sector or the clubs and organizations around football that I've been drawn to support There is a recurring pattern that I never think of creating intentionally but it has become increasingly clear to me as I have spent time reflecting on what the successful investments share with one another and what the failed ones have in common with each other. The pattern is not sectoral - it cuts across technologies, consumer services and sport. It is not structural - the pattern is evident in firms which have different ways of acquiring capital, structures for ownership, and operating models. It is nothing to do with market sizes or growth trends or the technology architecture that underlies the product. It is about character - specifically, what extent the company at foundation of the investment has the genuine, operational as well as consistent commitment to overall well-being and the development of people inside it, expressed not only in the things that the organisation says about itself but also in the choices it makes when it comes to saying the right thing and doing the easy thing do not necessarily mean the same.
I am aware that this observation sounds, straight up, something that is put on the walls of offices and the company's website pages, only to be ignored by those who ordered the work. I'm trying to make clear that I am not talking about the official version of the commitment to individuals - the values document, the approach to diversity and integration, the culture deck that was designed to enhance the effectiveness of hiring and that investor's pitch. I'm talking about the operational aspect: the decisions to be made throughout the day, if the principles articulated in those documents and the commercially or personal choice are in conflict and the company has to decide which governs. What I've seen in organizations that develop lasting value - not just impressive short-term performances but also the kind of compounding, long-term performance that yields exceptional longevity returns - tend to be those which have a solution to that issue is a given. Where the intention to do right by employees within the company is not contingent upon whether doing the right thing is the most cost-effective fast, fastest, or immediate-paying option.

It is about identifying prior to the time that an investment is taken, the ones that commitment is genuine than performed, where the culture of care and accountability is embedded into how an organization actually works rather than the way it describes itself - is, I believe, the foremost and difficult task in investing long-term. It's significant due to the fact that it is the factor that has the highest probability of predicting that kind of compounding performance that can yield truly extraordinary returns over meaningful time horizons. It's a challenge because you will not find it in a financial model, can't find it in a professionally-written management presentation, and you won't be able to pinpoint it even in comprehensive reference checks although these are helpful. You can find it by spending ample time with an institution, in enough different contexts and at enough different levels of hierarchy to determine how it acts when the situation is vague and nobody is paying attention. This kind of thoughtful engaged, exploratory interaction is difficult to implement into many investment processes, which is one of the reasons why most investment processes are less successful in identifying truly exceptional organisations than the majority of investors recognize or even discuss.

The connection between true organizational character and long-term performance is a connection that I believe more now, with more years of experience in longitudinal observation to my credit than I did in that point in my investment career. Organisations that care for the wellbeing of their staff consistently and which express that love through operational decisions, not only in culture and communications documents, typically outperform organisations that treat people exclusively as assets to be optimised. Not always in the short time - a company that maximizes the output of their employees through high pressure and high stress can be very efficient over a period for a number of months, perhaps even a few years, particularly in the context of an economy that is strong and compensates for internal dysfunction. But over a longer time frame those advantages of an environment that is truly a people-first one multiply with ways genuinely difficult to duplicate through or any other system. The amount of talent is increased because people with options - top performers - tend to prefer environments where they feel genuinely valued over environments that make them feel manipulated however, they do charge more. The institutional knowledge gets deeper because people are able to develop it instead of going through on a timeline is typical of high-pressure workplaces.

The decision-making quality improves because the people feel confident enough to bring up issues and to share bad information without considering the personal cost for doing so. This ensures that problems are identified and resolved earlier and less costly than in places where the message consistently gets shot. The organization's ability to adapt to changes in circumstances increases because people are invested enough in its performance to go over and above their formal obligations in situations that truly require it. These advantages are not individually dramatic. They're not an element that can be used to create a compelling storyline in an Investor Update or board presentation. However, they do build up and create a competitive advantage. This is genuinely hard for organisations that have weaker cultures to duplicate in the sense that the benefit is not linked to any particular product, process, or capability that could be observed and copied. It's located in the environment in which the business is run - in the quality of the atmosphere it has designed for the people inside it and in the quality of the decisions that people make as a result. This is the reason character, both in organizations and in individuals is not a soft notion. It is, in my opinion, the hardest as well as the most important thing of all.}