Keith Sherringham: Rather than one single thing, it is more a series of events over time, taking opportunities, responding to conditions, and adoption to circumstances which has occurred. Being drawn into technology and business transformation is more a reflection of a series of interests and passions, the wanting to bridge gaps, as well as from a desire to help and share experience and expertise with others. For sure, my thinking has evolved with experience and with time. Across the technology changes and advances we have seen, and of those still to come, my thinking has developed and matured with the help of the following: We change with our environments, our behaviours respond, and collectively and as individuals we realise emergent outcomes. The value of people and the human factor is paramount, but we often need our learned experiences to appreciate views and experiences of others. We are at our best when we are empowered, have ownership, our shared interests and values align, and we have pride in who we are and what we do. We respond to leadership which is the change we wish to see and who treats us as they treat themselves. We are better with support, skilling (the ability to do) and training (the how to do) which enables us to realise opportunities and adopt and adapt to circumstance.

Keith Sherringham: The experiences which had greatest influence are where I learned lessons from successes and mistakes, realising the importance of listening to people and their expertise, and the importance of making decisions but with response to changing circumstances. This is seen across leadership, people, process, data, and governance.

Keith Sherringham: Our response differs, as does our adaption, within organisation and within ourselves. While our approaches and experiences vary, there are common aspects, and seldom does the “one-size fits all” approach apply. The need is to work to emergent outcomes, bring changes in the environment, and instil the behaviours to enable empowered ownership. Organisations do adopt and adapt, though it may take time and it requires consistency and persistency of effort.

Keith Sherringham: There are different types of AI (GenerativeAI and AgenticAI or Robotics or IVR and ChatBots or ImagingAI and FacialRecognition and the aspirational Artificial General Intelligence – AGI). AI has existed in many forms for many years and is applied in different ways to business. Aspects like robotics have already delivered returns, are profitable, and bring known proven practices. Our use of AI (in its varying forms and integrated AI types) continues to be about growth, opportunities, new products and services, keeping customer trust, and protecting businesses (AI is About Growth, Opportunities, Revenue New Products, Service Openings). From a business side, there is not much that is genuinely new (what we do changes slowly but the how we do it changes quickly). We know what we need to do, we know how to respond, we know how to prepare, and we are proven in crafting and shaping the capacity and capability to adopt and adapt. It is about what we decide to do and how we do it. The proven business realities still apply. Business and society has faced comparable transformations, and will respond and realise betterment again, but what is different with AI is: the pace and rate of change in comparison to other technologies and societal changes; the amounts invested, where investments are being made, how the investments are made, and the acceptance of rate of returns; the differing approaches undertaken, the concurrency of impacts, and the transformational potential.

Keith Sherringham: We are seeing the AI-hype and AI-bubble play out. Our human nature, our vested interests, and the costs of incumbency are the realities we work with. We are seeing the short-term views competing with the longer-term needs. While each organisation is different and will make the decisions which it sees as in its best interests, we are seeing the commercial realities of business manifesting (e.g. slower take up of AI and deferred investment returns). The hype around job losses is also changing. The leaders in AI focus on real Needs, the Leadership to make the changes with decision making and response to circumstance, the People deliver the changes, they use the Processes, need the required Data, and some level of responsive, dynamic, and appropriate Governance is required (The Who, Why, What, Where, When, & How of AI).

Keith Sherringham: If there is one single thing, then it is the politics of delivering and realising change while maintaining business operations. The politics includes sovereignty (Crafting & Shaping the Sovereign Capacity & Capability for AI), being prepared to do what is needed, able to make the decisions and follow through, as well as being capable of realising what is needed. Working to the required time scale and for agreed returns is also required. Investment returns from AI and profitable AI are being realised when leadership has moved beyond the AI-hype and AI-bubble, where they are providing the relevant budgets, allowing time away from business operations, being prepared to fix processes, willing to engaged stakeholders, address the data regime, and mature governance.

Keith Sherringham: A business knows how to do this now. Decisions are made using the proven, pragmatic, practicalities of business. We and business leadership needs to move beyond the AI-hype and AI-bubble to value the human factor, realise the growth, the opportunities, the new products and services. Many are doing this, but it is about the realities outside of the AI-hype and AI-bubble and this is a specific decision we make. Within business, decisions are on a risk-based approach for business needs against objectives with the agreed strategies and approaches. The AI strategy of a business comes from its business strategy. The cost of AI implementation is the cost of migration (people, process, data, customers etc.) and not just the technology cost. The decision is about how to grow business and service customers with AI within a whole of business approach.

Keith Sherringham: This will vary with each business, the type, industry sector, size, location, markets, regulatory regimes, complexity, and investment time frames and returns. The performance of AI is measured and valued through the business outcomes delivered like any other business investment and activity (Protecting You and Your Business with Audit of AI). The typical business areas including revenue, customer retention, costs, staff engagement, and regulatory outcomes are assured whether AI is used or not.

Keith Sherringham: Business depends upon data and the flow of data across stakeholders. In this regard, AI is just another user of data within business. Cost, Sovereignty, Agreements, Access and Permissions, Supply and Availability, Regulatory and Legal, the Working Across Closed and Open Loop operations, Continuity and Backup, Quality, Allowed Use, and Safety and Security are all required of data before use in AI, during use in AI, and after use with AI. From data for training models to having data from AI returned to legacy systems, the need for good data with the respective metadata across the different data types and AI types exists within operations and services. Look at it this way, business processes from payroll, to report writing, to customer requests, to logistics and through manufacturing and food production; all need data to operate. The use of AI is no different, we just need to consistently and persistently apply the known proven pragmatic practices.

Keith Sherringham: The short answer is the business owner for the respective business deliverable. To add a little more, the ownership, custodianship, the roles and responsibilities, and the liabilities and accountabilities for the data remains with the human who is the respective owner for the business deliverable. Who cleans the data, assures data use, how this is done, the use of AI in data laundry, the processes used, the standards applied, the assurance regime utilised are all business and process specific and are required for AI. Now, should AI be treated as a user of data, with custodianship, roles and responsibilities, liabilities and accountabilities for data used and generated? The answer is yes. Does this approach bring legal issues? Of course there is, but the operational returns from this outcomes-based approach and use within frameworks is significant.

Keith Sherringham: Need, cost, leadership, and politics. Other factors include the skilling (ability to do) and training (how to do), time away from business operations to make changes, and undertaking revisions in processes are also required. The familiar data issues (cost, sovereignty, agreements, access and permissions, supply and availability, regulatory and legal, working across closed and open loop operations, continuity and backup, quality, allowed use, and safety and security) impact business and the application of AI.

Keith Sherringham: Business leaders having an appreciation of the role of data in business, the value of data, having data as an asset with its depreciation, the costs of data, and the business impacts from the use and application of data are the ones with an advantage. The need for data governance then comes from the leadership provided around data and data services within business (Governance for Data & AI to Assure Customers and Protect Business). Whether this is for existing business or for use with AI on a risk-based outcomes-based approach, data governance is about better business outcomes, lower costs, retaining customers, assured services, and protecting businesses.

Keith Sherringham: Short answer, the decision owner. Whether the outcome is good, bad, or indifferent, the business owner for that decision is liable, accountable, and responsible. When it comes to decisions within business, there is a reason why we do not allow a free for all-regime. We have governance with decision management, apply delegations, permissions are used, authorities are allowed, approval levels exist, and there is a commensurate governance regime. Our business governance regime extends to our use of AI and we assure the business and AI regime. Decision making is an emerging area of business opportunities.
• Business Embedded Governance for AI
• Delegations Regime to Assure AI Based Decision Making
• Automated Decision Making and Cyber Security
• Repeatable Customisable Process
• Working Across Open & Closed Loops

Keith Sherringham: The same regime we use for innovation within our business today, is applied to our innovation with AI. AI will also drive developments and improvements within our innovation regimes. Innovation can be encouraged within business through need, leadership, funding, allowing time away from operations, supporting process changes, enabling data regimes, and use of governance for better products and services. A risk-based approach, stepping back from cutting edge technology, with staged tactical incremental delivery to an overall strategy also helps. If there is one factor of impact, then it is the leadership and the resultant political regime experienced. From a board, to executives, to team leads, or people of influence, the environment which stifles innovation is through the casting of blame, the risk aversion, and the absence of incentives.

Keith Sherringham: Cloud providers, technology platforms and external AI models are a strategic risk, a sovereign risk, a market risk, an operational risk, a transformation risk, a people risk, a data risk, and a technology risk (amongst other risks) to business. Risks can be positive or negative. The risk-profile of a business will vary with type, industry sector, size, location, markets, regulatory regimes, complexity, and investment time frames. Factors like cost, business readiness and logistics chain integration are of impact and to the decisions made. The strategic risk of AI to business is seen now and is impacting across business operations, with the risk being direct or indirect. From the need to exit markets because of AI changes, to acquiring competitors, across the costs of implementation being prohibitive, through the cyber exposure and vulnerabilities, to workforce changes, and operational continuity; the strategic risk and the dependency risk of cloud providers, technology platforms and external AI models is impacting across business now.

Keith Sherringham: What does a business do with its other core and critical assets? Then why is data, technology, and AI any different? Our AI systems, our data, and our technology are core business functions, business dependencies, and business assets. Sufficient ownership, with the necessary skills and expertise, the agreements, the accountabilities and liabilities, and the support and operational arrangements are required.

Keith Sherringham: Introducing AI is part of transforming a business. Transforming a business requires time, money, and effort. Transformation needs the management of politics, leadership, resources, stakeholder engagement, time away from business operations, governance, revisions to processes, addressing data, and making operational changes. Transformation can impact customers, channel partners, vendors, and the regulatory and compliance regime of a business. Transformation requires people and business prerequisites (Having Requisites to Run and Change a Business on a Risk-Based Approach), with a support regime of readiness including skilling (ability to do) and training (how to do). Transforming a business requires decision making, response to circumstances, and consistency and persistency to deliver. Small tactical staged implementation of AI against an overall need and strategy is often applied. Using small projects to have us be comfortable is part of the approach. Transformation is very different to using AI in content generation and the copy and paste into documents or the making of presentations. Opportunities for business exist around this.

Keith Sherringham: While we deliver business change and any technology change (from the replacement of an operational server to a core systems replacement to a divestment or merger of a business) there is a requirement for leadership and having the necessary organisational regime with the appropriate governance for delivery. The vison, the decision making and the response to circumstance, including the engagement is needed from leadership. The importance of leadership is across boards, executives, team leads, peers, and with people of influence within an organisation (Outcomes-Based AI for Business).

Keith Sherringham: Much of business transformation, technology implementations, and the realisation of returns from AI are delivered by projects (change the business) while operations need to be maintained (run the business). The business realities around success in ICT projects have been reported many times, with typical causes for failure remaining consistent over time, across the complexities of projects, and business areas including: Stakeholder policies together with unrealistic or unarticulated project goals; Commercial pressures often leading to inaccurate estimates of needed resources and badly defined systems requirements; Inability to handle the project’s complexity along with poor project management and poor reporting of project’s status; Poor communication among customers, developers and end users which can result in sloppy development practices and unmanaged risks; Use of immature technology. Of these most common factors reported, just one is technology related. Politics, expectations, leadership, time, budget, and resources are the main human factors impacting projects and our take-up of AI (Getting the Best from People in Projects & Programs).

Keith Sherringham: Leadership is about vision, decision making, responding to circumstance, and engagement. Leadership is the change they wish to see and treats us as they would be treated. We see with the AI-hype and AI-bubble of the negativity, the cuts, the devalued human factor and this is an example of how leadership impacts. Similarly, we see leadership like Ikea (Instead of Laying Off 8,500 Workers Because of AI, Ikea Used This Radical Leadership Playbook to Grow Revenue) with a valuing of the human factor for growth, revenue, and profitability. Leadership is tasked with managing ambiguity, messaging the emotional bond, enabling empowered ownership, making decisions and responding to circumstance, and aligning interests and values. Through skilling (ability to do), training (how to do) and with support and mentoring, leadership achieves delivery by enabling us. Many report business opportunities around leadership for AI.

Keith Sherringham: AI has shaped and matured my thinking around knowledge worker processes and services. Overall, I see a positive and optimistic future full of opportunities because humans have the capacity and capability to adopt and adapt, and we seek to better ourselves. Sure, there will be changes and challenges, but we know how to respond and what to do. AI has strengthened my thinking around the importance of learning the lessons from other industries like manufacturing or food production or healthcare, and bringing this experience and expertise to our establishment, operation, and management of AI. Models like that of passport control and the pilot–auto-pilot model provide paths for realising returns.
• The AI We Need BUT! – AI Supporting Personality Profiles

Keith Sherringham: As AI is increasingly used, and as AI moves from the routine to the more complex processes and operations, the human factor is of greater importance across operations and services. The human abilities which we are expected to see more of around AI includes trades skills, through care services, to work in remote locations, to services where people are needed for managing relationships and intervene to problem solve. Human abilities are increasingly needed when errors are to be remediated and exceptions managed, where an integrated response across diversity of stakeholders is required, and where appeals to human traits are required (The Human Factor Within AI Brings Returns, Profits, and Growth). Other areas requiring critical thinking, problem solving, and being able to create for the first time see increased demand for the human factor and of the professional skills (like people management, financial management, vendor management, relationship management, strategy and planning, risk management, project management, problem solving, management of change, management of ambiguity, governance, compliance management, cross-disciplinary collaboration, and communication and presentation).

Keith Sherringham: What do we need for growth, opportunities, new products and services? History shows us that technology changes have differing impacts across societies and businesses. We can see the lessons from history impacting now. We are seeing some jobs lost, jobs can be relocated, jobs and services occurring in different locations, jobs being created, jobs changing, but with jobs often becoming more complex requiring more skills and expertise (Role Advances with Artificial Intelligence). While we may not know the future, or how it will work out, we know there are opportunities, and we know certain things are expected including: The AI-hype and AI-bubble of cuts, devalued human factor, and massive job losses in short periods is seldom the business reality; We have the skills and expertise to prepare and respond ongoing to AI; That people are important and that when we are part of the process and feel valued, sustainable changes are realised; Skilling (ability to do), training (the how to do), and with support, is how we get better outcomes; The professional skills are of increasing need.

Keith Sherringham: In essence, apply the known proven pragmatic practical realities. Don’t wait, work on crafting and shaping the capacities and capabilities to adopt and adapt. Trust your people. Bring ownership, leadership, and sovereignty. Apply your good business regime to AI and realise opportunities. What we need to do for our business and what we need for these opportunities stands out: Sovereignty; AI for Purpose; Integrated AI Types; Specific Need; Integration; Help Us to Help Our Selves; Lower Costs.

Keith Sherringham: Skilling (the ability to do) and training (the how to do) often go together and both are needed across business for the use and application of AI. Returns will come and opportunities will be realised because of the professional skills we bring to the opportunities we create and realise. Much of AI should become seamless to many users, and we should just use the applications, the processes and the workflows, the data supplied. We should not need to be concerned with AI directly, but the business outcomes. AI should be smart enough to ask questions of us (Having AI Ask Us Rather Than We Prompting) to deliver outcomes rather than us learning the prompting of AI. The greater need is for the advancement of the professional skills.

Keith Sherringham: Simply put, NO. The technical skills are not enough. Of course, technical skills are important, especially in certain roles, but these technical roles also need the professional skills as are required across the rest of business. The overall need is for more people with greater skills and expertise, with stronger professional skills, and with the capacities and capabilities to adopt and adapt to enable business and to realise opportunities. Judgement, communication skills and leadership are all required, especially as processes are automated and the decision management regime is extended to AI.

Keith Sherringham: From managing AI written work in assignments, to plagiarism, to quality assurance of results, to preparing students for the future; the answers are known. It is the business realities, the resource mixes, and the time to change which intervene and keep the educational status quo. Pick the example of coding. AI can write the code, but the teaching of requirements and business understanding, the enabling collaboration and stakeholder management, the application of testing for validation, and assuring business readiness are all beyond what AI can currently do (Educational Response to Emerging Needs Around AI).

Keith Sherringham: Technical skills are important, but the fundamentals rather than a specific technology are more important. In addition, the professional skills are of greater importance. Learn how to sell and engage, have skills in managing cashflow, be able to service customers, and deliver products and services. When we have a problem, our first question is “who do I know that can help?”, so careers are about: Direct engagement of people you know; Act with your leadership and create opportunities rather than waiting for others; Mentor and volunteer to help build contacts and experience and expertise; Network with and meet others as it not what you know but who you know; Support by working with people to support you and support others.

Keith Sherringham: AI is intensifying the need for a whole of business response across cybersecurity (Cyber Security and Us – Meeting the Demand, Services, and Growth) as we experience more attacks, occurring faster, of higher frequency, across extended points of vulnerability, being of greater duration with increased complexity. There is also more integration exposure across systems, extended data impacts, with vulnerabilities across the distribution chain and value stack. With AI proliferating the use of shadow technology there is a corresponding cyber risk increase, the use of AI agents provides more vulnerability, and the need for the human factor is of greater importance (Cyber Defense Magazine – AI Within Cyber Security).

Keith Sherringham: There are many sectors like manufacturing and agriculture which have led in automation, processes, data practices, and governance regimes. The healthcare sector with its complexity of stakeholders, the extended logistics chains, the diversity of integrated services, and the extent of interdependencies within regulatory regimes has many lessons to bring to other industry sectors. Some of the lessons we see include: The role and importance of systems integration across logistics chains; The value of records sharing and management; Management of permissions and data use across stakeholders; Managing non-linear and splintered data within business processes and decision impacts; Supporting the integration of data types and metadata for services; Taking a risk-based approach to data and with AI; Leadership in working with open-loop and closed-loop operations and services; The role of human factor and the need for business prerequisites.

Keith Sherringham: The balance in innovation with safety and human oversight is nuanced and varies with business. The balance is achieved through the consistent and persistent application of proven pragmatic business practices with ongoing review and improvement. Leadership, strategy, budget, resources, risk-based approach, decision-making and response to circumstance are all needed. Any regime seeking to balance innovation, safety, and human oversight needs to address operational aspects like Near Misses, Major Losses, Gap Intensification, and Reduced Response.

Keith Sherringham: Both. AI is playing a mixed role in cyber security and this is set to continue. AI is used for staging and exploiting attacks, while also being used preventively and defensively. From sacrificial digital twins to protect legacy systems, to orchestrated AI agent defensive approaches, AI is set to play a prominent role within cybersecurity and drive the sovereignty required (Sovereign Cyber Security – Meeting Demand for Cyber Security Around AI).

Keith Sherringham: This move from content generation to automation of processes and decision making with AI can bring significant operational changes as well as many opportunities for cost savings, improved customer services, and sales for service providers. For some businesses there will be little changes in how they think about AI, while for others, it is substantive. The fundamentals of need, leadership, people, process, data and governance continue but some changes may include Opportunity, Advancing People, Stakeholders, and Business Realities.

Keith Sherringham: Businesses are set to experience a range of risks across people, process, data, as well as in the logistics chain and value stack. While the specific risk-profile will vary with a business, one area of greater risk is that of the management of decision-making with the use of AI as we automate processes. This includes strengthening current governance regimes and extending regimes to AI as well as the use of AI in revising business governance. One of the main areas of risk for AI agents is cyber security (How We Hacked McKinsey’s AI Platform) and the related vulnerabilities.

Keith Sherringham: Yes to all three. These can be positive or negative outcomes, with direct or indirect impacts, but it will depend upon what we decide to do and how we implement. The tendency to rely on AI and just accepting answers from AI is already an area of risk and is bringing organisational changes. The impacts of AI are occurring now, are becoming more frequent, are set to be more extensive, and of increasing consequences (FTC Privacy Restrictions and Social Media Impact).

Keith Sherringham: The extent, the details, and the response will vary with business but some common aspects to enable across business includes: Technology Environment; Permissions; Awareness; Approved Agents; Testing (Valuing Testing within Artificial Intelligence). Such measures apply across personal and business environments, whether the status is development, test, production, training, or backup environment.

Keith Sherringham: Businesses are well served when: The importance and value of people within business are core; The realities of the proven pragmatic practicalities of business and there consistent and persistent application occur; Growth, opportunities, investment returns, new products and services, and keeping customer trust while protecting our businesses are realised; A whole of business response is taken to transformation with an acceptance of the time to change, and the consistency and persistency needed.

Keith Sherringham: I think the most important changes are the growth, opportunities, and new products and services. The new businesses which will emerge, the changes in markets resulting, the business advances which we will experience, and the furthering of our pride and professionalism in who we are and what we do. We will realise these because of what we decide to do. Operationally, as AI becomes the new business layer, it is the changes in processes with data services and flows which are set to be of impact.

Keith Sherringham: The upcoming and those in the future are better able to answer this one, and I expect that many of the exaggerations of the AI-hype and AI-bubble with its negativity will play out and should move quickly into history for lessons learned. The sooner our conversations move to the importance of the human factor, growth, opportunities, new products and services, greater skills and expertise, retaining customer trust, and protecting business; the better we will all be.

Keith Sherringham: Any one piece of advice is often of value with shared and similar experiences and context, but let us share the following: For Business leaders – Craft and shape the capacities and capabilities for adoption and adaption and we all benefit; For professionals – It is about being right, at the right time, with the right amount of influence (money), with the right people; For young people – Build professional skills, grow your network of contacts, find a mentor to work with and mentor others.