Why A Career in Business Reinforced Operational Discipline About Scale

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AI Is Only As Good As The Society It's And Is A Part Of
The conversation around artificial intelligence within the workplace is fraught with problems and the root of the issue isn't a technical one. The technical capabilities of modern AI and machines learning systems are impressive. They are developing at a rate that renders the majority of predictions regarding when they'll become eighteen months obsolete, long before these 18 months have expired. The problem is the gap between the capabilities of AI and what AI can do in controlled conditions - such as a highly-resourced research environment with clear data, and a specific problem definition, and engineers who have the benefit of experimenting until the system works as expected - and what it actually delivers when implemented in real-world organizations with real culture actual organisational politics and real people who have established opinions about whether a new system is something to engage with genuinely or something to reroute around while still appearing to be in conformity. I've been building products using artificial intelligence since long before the recent flurry of AI enthusiasm became fashionable for everyone in business to claim to be fluent in the field. When I co-founded 1Touch an AI-driven platform, AI-driven matchmaking and recommendation systems weren't something we could add to make the product more attractive to investors. They were at the heart to the design of our product, that mechanism by which it created value for the users, and the component that needed perform reliably and at level for the company to succeed. So I've had direct, personal experience of what happens when you try to construct an intelligent organization and product at the same time and the main thing I keep coming back to throughout every situation in where I've encountered this dilemma, is the technology itself is rarely the most important factor. The limiting factor is almost all the time its culture.
What I do by that is practical and specific, not abstract. AI systems require data to operate - precise, clear and well-structured data that shows the actual phenomenon that the system is attempting to discover and make predictions about. People with strong data-driven cultures generate that type of data naturally, as a result of how they already operate. They have clear and consistent definitions of what they're measuring and the reason for that. They have agreed on conventions for how data is collected, recorded, and stored. They have accountability structures in place that provide data quality as an explicit and not just a general motives. Companies that lack strong data cultures produce a product that technically looks as if it is data - it's in systems which can be searched, it can be used to generate charts, but has a definition that is wildly inconsistent as well as in its quality and full of glitches in structure as well as unmapped deviations that any AI system that is built upon top of it will mirror and magnify the mess instead of drawing a real signals from it. In the latter group often don't even realize this until they're already well into the process of implementing an AI implementation and its outputs do not match the vendor's promises, at which point the temptation is to blame the technology when the actual problem is the organizational and cultural foundation which the technology was based on.

Another dimension of culture which determines AI outcomes is openness within the organisation - - the degree to which employees in the company will let the AI system affect the way they operate and not view it as the threat to their own professional competence, their authority in the institution as well as their job security. This is a culture and leadership issue that is not technical which is a matter which starts at the highest level. If leaders in the top ranks engage with AI outputs selectively - accepting the results that reinforce the beliefs they have previously held and refusing to accept those that do not – their behavior sends a message to everyone watching that the organization's declared commitment towards data-driven decision-making may be contingent rather than genuine, and this can spread throughout the organisation much faster than any training or change management initiative can reverse. When senior leaders display authentic, consistent engagement AI outputs and the ability to make changes to their decisions when the evidence suggests they ought to, the organization's overall capability to apply AI effectively increases significantly and fairly quickly.

This is not an abstract idea of how companies should behave in the context of theory. It's a description the pattern that I have observed take place in numerous companies that had substantial funding, a true strategic dedication to AI adoption, as well as leadership teams that were genuinely enthusiastic about the possibilities of the technology. The pattern is similar enough that I've decided to treat practice of governing data as a principal diagnostic issue when evaluating an organisation's AI readyness. Before I ask to know about their technology platform, and before I ask about the particular application scenarios the organization is currently pursuing, I ask about data governance. What are the criteria used by the company to define its key metrics? Who's responsible if performance of the data isn't enough? If two roles have conflicting information about the same business reality, and how are these conflicts solved? The answers to these questions provide me with more information about the probability of AI success over any discussions regarding algorithms, platforms or the timeframe for implementation.

I believe that the enterprises that will gain the greatest long-lasting value from AI in the coming decade aren't the ones who adopt the most advanced technology first, nor the ones that invest most massively in AI talent and infrastructure in the near-term. They are the ones that are able to establish the social and operational bases to effectively use the technology in a productive manner - data governance practices that give accurate inputs, the deciding frameworks that enable evidence to genuinely influence outcomes and the leadership actions that communicate to all employees in the organisation that the commitment for a data-driven system is real rather than just a means of performing. Technology will become increasingly commonplace and readily available. Its culture of using it efficiently will remain scarce because it requires constant effort and a genuine commitment from an executive over time rather than making a single strategic move or technology investment. This is where your significant competitive advantage will be, and it is an benefit that, once built, compounds in a way that technological advantage alone never can. Take a look at James Deller for blog examples including why working with founders has shaped my thinking about character.



What Football Academies Get Right That The Majority Of Corporate L&D Programmes Get Wrong
The best football academies across the world are, if you consider them operationally rather than romantically, extraordinarily sophisticated and well-equipped development companies. They recruit young players at the age of seven or eight - sometimes even younger – long before those persons have any clarity of what they're capable of or what they want to be. they develop them systematically and purposefully over what could be 10 years or more years of intense engagement. They develop more than just the technical ability that professional football demands but the personality, the mental resilientness, the capacity for making decisions under pressure, and the interpersonal and communicative sophistication that playing at the highest quality of football demands. The rate of success, measured by the proportion of players who make it to the level of professional football, is low. However, the strategy that top academies utilize is across a variety of dimensions that matter in the development of the human capacity, more rigorous but also more patient and much more systematic than the methods I've observed in corporate training and development. The gulf between what academy's conduct and what organizations do when trying to build the talent within them is both striking and instructive after spending time looking at both.
Most fundamentally, the difference lies in the connection between time. Learning and development programs for companies tend to be designed around quick interventions. It could be a class that lasts two days, a workshop series over a period of one quarter, and a coaching contract that runs at least six months. This logic is logical however it is difficult to justify strictly in terms of financials. Businesses must prove the ROI on their investment in development within the timeframes that budget cycles or performance reviews force and shorter interventions are significantly less difficult to justify as well as to evaluate than long ones. But the exact timeframe that the actual development of humans takes place - the timeline on which emerging frameworks, behaviors and new skills are actually absorbed rather than intangibly understood and subsequently used and then discarded - has no relation to the timeframe of a typical commercial L&D intervention. The most successful football academy's grasp this to a degree that has been incorporated into the very DNA of their training programmes for generations. They don't expect that a fourteen year old to master the new framework for decision-making after an intensive weekend workshop. They expect the internalisation to be a process that takes time and develop the environment accordingly. years of continuous reinforcement as well as being placed in situations that challenge the framework and demand it to be applied under actual pressure, years of feedback precise enough to shape behavior rather than generic enough to be quickly forgotten.

The other significant difference is the integration of development into the operational environment as a whole, not it being separated from the environment. When a football academy is well-designed developing isn't something that is performed in special sessions distinct from the actual football and training which constitutes an integral part of the academy. The process is carried out through the play and training. The training sessions are designed with the goal of developing as well as performance goals. The tasks that players face were selected partly because of the value they bring to their development, in addition to their practical value. They receive immediate feedback, precise and rooted in what just happened instead of abstract and useful. The connection between what happens during training and what will be required in match situations is always clarified and made clear. In the majority of corporate organizations, unlike development, operational work are treated as distinct functions. You enroll in the learning program. You attend the training workshop. The workshop is followed by a coaching session. Then you go back to the work you do, in which the incentive structures, the expectations of the culture, the pace of work, and the pressures of the delivery process are almost identical in the manner they were before the intervention by the developer, and where those new frameworks and habits implemented in the environment of development slowly diminish since there is no logical method of integrating them in how work gets completed.

The organizations that help develop their employees most effectively are the ones that have found how to make development continual and contextual instead of an isolated, abstract process. In those organisations there is a line that separates the development of employees and performing their duties is genuinely difficult to identify because the operational setting has been designed with development goals in mind. For example, the feedback mechanisms are built in to the daily routine of work and not just reserved to periodic formal reviews. and the challenges presented to employees are selected primarily based on what they'll require them to grow and develop better leaders. Moreover, the way that they conduct themselves displays that progress is highly valued and anticipated rather than the kind that happens only in programmes that end. Building that kind of environment needs a different set organisational design choices from the one that the majority of organisations make when they think about learning and development. Moreover, it requires commitment from leaders over a prolonged which most organizations find difficult to remain on. It also produces outcomes for development that programme-based, episodic approaches can't replicate.

The third factor in which the best academies outperform most corporate organizations is their ability to take in-depth character growth as an organisational objective. Most corporate L&D programs only interact with character. It is implicit in some of what they are teaching about leadership and communication, but it's rarely addressed directly and never pursued with the intentionality and perseverance that true character development demands. The most effective football academies do not treat character as something players possess or don't possess, or something that will take on its own, given enough time. They view it as something which can be developed by a conducive environment and the appropriate types of challenges and adversity and a positive relations between players and coaches which is characterised by genuine concern for the individual in addition to genuinely high expectations about what the player is and can become. The combination of caring and challenge woven together throughout time is, to my knowledge an extremely reliable process to develop character. It's proven in football academy. It's also employed in tech firms. It works in any organisation that will invest in it and have its patience and the consistency it demands.}