AI Is Only As Good In The Culture It's Built Into
The discussion around artificial Intelligence within the workplace is fraught with problems and the cause is not technical. The capabilities of modern AI and machine learning technologies are remarkable, growing at a speed that renders many predictions of when they'll become eighteen months obsolete well before the period of eighteen months has expired. The issue is the gap between the what AI can accomplish under the context of controlled conditions in a thoroughly-equipped research setting, with clean data, with a clarified problem statement, and engineers who have the luxury of continually testing until the system can be used as designed - versus what it can actually deliver when it is implemented within an actual business with real people and real-world organisational politics and people with established opinions about whether the new system is something to take seriously or something to navigate around in the name of compliance. I've been building products using Machine Learning since well before the wave of AI enthusiasm became fashionable that everyone in the business world assert their competence in the field. When I founded 1Touch AI-driven matchmaking and recommendation systems weren't something we could add to make the product more appealing to investors. They formed the basis element of our product's structure, being the primary mechanism that the platform was able to create value as well as the feature that had to function reliably and at level for the company to remain viable. Therefore, I have direct practical experience of what can happen as you try to implement something truly intelligent into company and a product simultaneously and what that I will always return to each and every circumstance in where I've encountered this challenge, is that the technology will never be an issue. It is ever the company culture.
What I say is precise and practical instead of abstract. AI systems require data to function properly. Clean, consistent well-structured and structured data that describes the situation it is trying to learn from and draw conclusions about. Organizations that have strong data culture create that kind of data easily, a natural result of the way they work. They have clearly defined and consistently implemented definitions of what they are analysing and why. They have agreed on conventions for how data is collected, recorded and stored. They have accountability structures that make data quality someone's explicit responsibility rather than everyone's vague intentions. Organizations that do not have strong data culture produce something that technically looks as if it is data - it's in systems, it can be queried or used to produce charts - but is so ambiguous in its definition as well as in its quality and brimming with defects in structure, and non-mapped anomalies that any AI technology that is constructed on the top of it will take advantage of and enhance the mess, instead of extracting real signal from it. These organizations in the second category are often unaware that they exist until they are well into the process of implementing an AI installation and the results don't match the vendor's promises. At that point the temptation is to blame the technology when most of the issue lies with the organizational and cultural foundation the technology was built on.

The other dimension of the culture that determines AI results is the degree of openness in an organisation - - the degree to which individuals within the company are truly open to letting an artificial intelligence system shape their work practices instead of treating it as the threat to their own professional know-how, their institutional authority or their security at work. This is a social and leadership issue not a technical issue and one that begins at the high levels. If senior leaders respond to AI outputs selectively, embracing the results that reinforce what they already believed and refusing to accept those that do not – their behavior sends an indication to anyone who is watching that the organisation's stated commitment to decision-making based on data is a conditional rather than true, and this conditionality will be passed across the entire organization much quicker than any program of training or change management project can combat. If leaders demonstrate real and consistent engagement with AI outputs that include the ability to make changes to their decision-making when evidence suggests they should, the organisation's collective capability to utilize AI efficiently improves dramatically and is able to be done so quickly.

This isn't an abstract consideration of what organisations should do in the context of theory. This is a description my experience of watching the same pattern develop repeatedly in organizations that had significant finances, real strategic dedication to AI implementation, and leadership team members who were completely enthusiastic about the possibilities of the technology. The pattern is so consistent that I have decided to consider guidelines for data governance as my essential diagnostic element when I am evaluating any company's AI capabilities. Before I inquire questions about technology, and before I ask about what specific application cases the organisation is pursuing, I ask about data governance. What defines the organization's its primary metrics? Who's the responsible party when quality of the data isn't high enough? If two areas have conflicting data concerning the same real-world business scenario, and how can the conflicts solved? The answers to those questions will reveal more about the chances of AI success as opposed to the endless debate about platforms, algorithms, or the timeframe for implementation.

I believe that those businesses that will reap the most durable value from AI over the next decade are not the ones who adopt the most advanced technology first, nor the ones who invest the most massively in AI talent and infrastructure over the next few years. They are the ones who put in the right cultural and operational bases to effectively use the technology properly - the data governance practices that give reliable information, the decision-making frameworks that provide proof that actually influences outcomes and leadership behaviors which signal to all people in the organization that the commitment for a data-driven system is real rather than merely functional. Technology itself will become increasingly commonplace and readily available. Its culture of using it well will remain scarce, because it takes a steady efforts and commitment from leaders over time, not the single strategic choice or a technology investment. This is where your true competitive advantage lies, and it is an advantage that once created and consolidated, will be able to multiply in a way that purely technological advantages never will. View James Deller for blog tips including how advising growing businesses shifted my priorities about teams.



From Commerce to Character Why the Businesses I Back all have one thing in Common
As I examine all of the investment actions I've been involved in the last few years - including the technology businesses and consumer companies, the investment opportunities in the emerging sector along with the associations in and around football that I have been drawn to there is a consistent pattern that I never intend to invent but has become more evident as I have spent time reflecting on the traits that successful investments share with one another and what the ones that fail share with one another. The pattern isn't strictly sectoral in nature, it runs through technologies, consumer services as well as sport. It's not necessarily structural. it can be seen in companies with different models of ownership and capital, the operating frameworks, as well. It is nothing to do with market sizes or development trajectory or the technology platform that powers the product. It's about character. specifically, about whether the company at the focus of the venture has the genuine, operational and ongoing commitment to well-being and development of its employees within it, reflected not just in what is said about the business but also in the choices it makes while doing the right thing while doing what's convenient do not necessarily mean the same.
I'm aware that this may sound, at first glance, like something that is posted on office walls and corporate mugs and pages only to be systematically left out by the folks who commissioned it. Let me be clear to clarify that I'm talking about the stated version of a commitment to people - the values document, the diversification and inclusive strategy the culture deck which was designed to enhance the effectiveness of the hiring process and it's investor pitch. I'm talking about an operational aspect: the decisions that are taken each day, as the principles laid out in those documents and the commercially, or personally convenient option come into conflict and the business has to determine which determines. The companies I've seen have created truly durable value - not just spectacular short-term results but the kind of compounding, long-term performance that produces exceptional long-term returns - are consistently those where the answer to this one is easily determined. When the determination to do right by the employees inside the organisation is not contingent on whether doing the right thing is the most cost-effective and fastest or quickly profitable option.

Find those organizations and then identifying before any investment is taken, the ones this commitment is authentic rather than performed, where the ethic of accountability and care can be found in the manner in which an organisation operates than the way it describes itself. It's, I think, the key and difficult task when it comes to long-term investing. It's significant because it's the attribute that has the highest probability of predicting what kind of compounding performance that results in truly remarkable gains over long-term time frames. This is because it is not in any financial model, won't see it in professionally-written management presentation, and there is no way to reliably locate it even with thorough reference checking, although those help. You find it through spending enough time with an organization in various contexts as well as at various levels of the hierarchy, to determine how it behaves when circumstances are ambiguous and nobody in particular is watching. This kind of thoughtful engaged, exploratory interaction is challenging to implement into financial processes. It is one of the reasons the majority of investment strategies are not successful in identifying truly exceptional organisations than they usually acknowledge or discuss.

The link between a genuine organisational character and performance over the long term is a fact which I am more certain of today, with than a decade of longitudinal observations behind me, than I did at starting my investment career. Organisations that pay attention to the needs of their employees continuously, and demonstrate that care in operational decision-making, not solely in culture and communications documents, tend to be more successful than those who view people more as resources that must be optimized. Not always in the short time - a company that maximizes the output of its staff through high pressure and high levels of insecurity may appear extremely efficient over a span between a few months and even couple of years, especially when that time frame is accompanied by an environment of market strength that takes care of internal issues. In the long run it is evident that the advantages of an environment that is truly a people-first one multiply and are impossible to replicate using another method. The density of talent increases because people with options - the most talented people - tend to select environments where they feel truly valued, as opposed to environments where they feel exploited and even when they pay higher. The institutional knowledge gets deeper because the employees stay long enough to develop it rather than cycling across the timeline high-pressure settings tend to create.

The decision-making performance improves since employees feel safe enough expose problems and communicate bad news without calculating the personal cost to do so. This results in problems being identified quickly and addressed less cost than they would be in places where the message consistently gets shot. The organisation's ability to adapt to changing conditions improves as the employees are so invested in its success to go beyond the boundaries of their job when the situation demands it. Each of these benefits is individually dramatic. They're not comparable to what creates a compelling story in the form of an update to investors or a board presentation. They do however, over time, build to create a competitive advantage. It truly is hard for companies with weaker cultures in the sense that the benefit is not rooted in a specific product, process, or capability that can be observed or replicated. It's part of the structures of how an organisation operates, in the level of the culture that it has created for people inside it and in the decision-making process those people make as a result. The reason for this is that character, within organizations as well as individuals, is not a soft notion. In my experience the hardest and most important factor of all.}