How Working with Founders Changed My Approach About Culture

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AI Is Only As Good As The Environment It's Created Into
The debate over artificial intelligence for business has a glitch The issue is not technical. The technical capabilities of modern AI and machine-learning systems are astonishing, and growing rapidly, making most predictions of the state they'll be in eighteen months obsolete even before those eighteen months have elapsed. The problem is the gap between the capabilities of AI and what AI can do under restricted conditions - in thoroughly-equipped research setting, with good data and a specific problem definition, and engineers that have the privilege of iterating until the system is working as it should - and what it actually delivers when it is used in real organisations with real cultures as well as real organisational policies and people with their own well-established views about whether a new technology is something to engage with genuinely and not something to maneuver around but still presenting as compliance. I've been working with technology for machine learning long before this current flurry of AI enthusiasm made it fashionable for businesses everywhere to claim fluency in the space. When I co-founded 1Touch in the year 2000, AI-driven matching as well as recommendation systems were not a distinctive feature we added to make the platform more compelling to investors. They were the core to the design of our product, the way in which the platform was able to create value and also the element that needed to be reliable and operate at an appropriate scale in order for the business's viability. So I've had direct, hands-on experience of what happens when you attempt to integrate something that is truly intelligent to a firm and a service simultaneously The thing I continue to revisit at every time which I've encountered this kind of challenge, is that the technology is not always the sole factor. The primary factor that is limiting the process is almost always the culture.
What I am referring to is specific and practical rather than abstract. AI systems require data in order to work properly - a clean, consistent properly-structured data which shows the actual phenomenon that the system is trying be able to learn from and make predictions about. Organisations with strong data cultures produce that type of information from the beginning, as a result of the way they work. They have clear and consistent definitions of what they are tracking and the reasons for it. They have agreed on conventions for the way data is recorded, collected, and stored. They have accountability systems that give data quality an explicit obligation, not everyone's vague motives. Organizations that do not have strong data culture create something that technically appears similar to data - it's in systems that are able to be examined, it can be used to produce charts - but the definitions are so different, and therefore variable in quality and full of problems with structure and non-mapped exceptions that any AI technology that is constructed on over it will mirror and magnify the mess instead of obtaining a real signal from it. These organizations in the second segment often don't realise this until they're well into the process of implementing an AI installation and the results do not match the vendor's promises, at which point the temptation is to blame the technology when most of the issue lies with the organizational and cultural foundation the technology was built upon.

Another aspect of culture that is the determinant of AI outcomes is organisational openness - the degree to which employees within the organization are willing to let the system influence or alter the way they operate instead of interpreting it as the threat to their own professional skills, their authority within the institution or even 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 which starts at the highest level. If senior leaders respond to AI outputs only in a selective way - embracing the ones that confirm what they already believed and ignore those that are not – their behavior sends the impression to everyone who watches that the firm's pledge to decision-making based on data is a conditional rather than true, which will then spread throughout the organisation more quickly than any training program and change management initiatives can reverse. If leaders show an authentic, consistent approach to AI outputs, which includes the reluctance to alter their decisions when the evidence suggests that they must, the whole organization's capability to utilize AI effectively improves substantially and relatively quickly.

This is not an abstract notion of how organizations should act in the context of theory. It is a description of the pattern I've witnessed unfold in numerous organizations that had significant funding, a true strategic commitment to AI implementation, and leadership teams that were truly excited about the possibilities of the technology. The pattern is consistent enough that I consider these practices as a primary diagnostic question when I am evaluating any company's AI potential. Before I ask for information about the stack of technology and before I ask about the particular uses cases that the organization is currently pursuing, I ask about the governance of data. What is the definition of its primary metrics? Who's responsible when performance of the data isn't enough? How do you handle situations where two roles have conflicting information about the same business situation, and how can these conflicts be resolved? These answers are more relevant to the likelyhood of AI achievement than any amount of discussion about platforms, algorithms, or timeframes for implementation.

I believe that the businesses which will create the most lasting value from AI over the next decade will not be those who implement the most advanced technology first, or the ones that will invest massively in AI infrastructure and human resources over the next few years. They will be the ones who develop the culture and operational frameworks that allow them to implement the technology effectively. This includes the data governance practices that give solid inputs, the decision making frameworks that provide proof that actually influences outcomes and the management behaviours that show everyone in your company that your commitment for a data-driven system is real and not just a flimsy performance. The technology itself will become more and more accessible. But the mindset that allows it to be used well will remain scarce, as it demands a constant effort and real commitment from leadership over time rather than an individual strategic decision or technology investment. This is where the real competitive advantage will sit and it's an advantage that once created is able to grow in a way that technological advantage alone never can. Have a look a James Deller for blog examples including why working with founders has shaped my thinking about real value.



From Commerce to Character Why the Businesses I Back All have one thing they share in Common
When I look across the complete spectrum of investment involvement I've been in over the past several years - the technology companies in addition to the consumer-oriented companies, the investment opportunities in the emerging sector along with the associations in and around football which I've been drawn to support There is a recurring pattern which I didn't set out to create deliberately but has become more obvious to me as have spent time reflecting on the characteristics that successful investments share with one another, and also what the ones that don't work share with each other. The pattern isn't strictly sectoral in nature, it runs through services, consumer products, technology as well as sport. It's not structural, it's seen in companies that have very different structure of ownership, financial profiles or operating model. It is in no way about the size of market or development trajectory or the technological architecture underlying the product. It is about character - specifically, whether the organization at the base of the investment shows the genuine, operational and constant dedication to the well-being and development of its members within it. This commitment is expressed not only in the things that the company says about itself but also in the decisions it makes by saying the right way and doing the convenient thing is not the same.
I know that this comment sounds, in its plain form, the kind of thing that gets published on office walls, workplace mugs as well as company web pages. It is subsequently overlooked by the individuals who made the decision to commission the work. I'd like to emphasize that I am not speaking about the stated version an obligation to people - the values document, the strategies for diversity and inclusion as well as the culture document that was created for the purpose of the hiring process, and investors' pitches. This is the decision-making process: the decisions which are taken, every day, when the principles articulated in those documents as well as the commercially or personally convenient option come into conflict and the company has to decide which one actually governs. Organizations that I have witnessed provide lasting value not just the kind of impressive short-term performance but also the type of compounding growth that provides exceptional long-term profits - are the ones where the answer to this question is predictable. Where the commitment to doing right by the employees inside an organization is not based on whether doing so is also the cheapest quick, most efficient or immediate-paying option.

Recognizing those companies before any investment is done, the ones in which that commitment is genuine rather than executed, where the ethic of accountability and care can be found in the manner in which the business actually operates, rather than in its description of itself. This is, I consider, the most crucial and most difficult ability when it comes to long-term investing. It's crucial because it is the quality that can most accurately predict this kind of compounding performance that provides truly extraordinary yields over time. This is because you will not find it in any financial model, are not able to find it in a professionally prepared management report, and you are not able to locate it even in a thorough reference check, although those help. It is discovered by spending enough time with an organisation with enough contexts as well as at various levels of its hierarchy to understand how it behaves when a situation is unclear and no one is watching. That kind of patient engaged, exploratory interaction is hard to integrate into investing processes. This is one reason that most investment processes are less efficient in identifying truly exceptional organizations than investors are able to recognize or even discuss.

The relationship between genuine organisational character as well as long-term performance is one that I believe more strongly now, with more years of observation over time behind me as I did at that point in my investing career. Organizations that are committed to taking care of their workforce consistently and show that care in operational decisions rather than just in communications and culture documents, generally outperform the ones that treat people principally as resources that have to be optimized. This is not always true in the short duration - an organization which makes the most of its workforce through high pressure and a high level of security can appear highly efficient over the course of a few months, or even couple of years, especially when that period coincides with a robust market environment that overcomes internal flaws. But over longer times in time, the benefits of a truly people-focused culture multiply in ways that are difficult to replicate by any other way. The number of talented people increases as the people with options – the most successful people - tend to prefer environments where they feel valued and respected over those who feel undervalued regardless of whether they pay higher. The institution's knowledge grows as people stay long enough to develop it rather than cycling through on the timeline that is typical of high-pressure workplaces.

The decision-making process is more efficient because employees feel safe enough be able to bring issues to light and share negative news without thinking about the personal costs to do so. This means that problems get identified and addressed sooner and less costly than in organisations where the messenger reliably gets killed. The ability of an organization to respond to changes in the environment improves since people are invested enough by its achievements to take on beyond their formal responsibilities in situations that truly require it. All of these advantages are individually significant. None of them is an element that will create an intriguing narrative for an investment update, nor board presentation. However, they do build up to create a competitive advantage that is extremely difficult for organizations which have weaker cultures because the advantages are not linked to any particular product, process, or capability that can be observed, or copied. It is located in the nature of how the company operates, in the character of the place that it has created for employees and the quality of decisions that people make as a result. That's why character, inside and outside of organizations isn't a delicate idea. It is, in my experience, one of the most difficult as well as the most important thing of all.}