Digital Transformation Beyond 2025 — The New Operational Paradigm (Part 1)
Introduction to the Series
In recent times, I’ve been writing extensively about key developments in AI — everything from how (and if) we should be using AI for tax, to its uses in therapy, to the results of giving a language model the keys to a retail business. These pieces all looked at the application of AI in the real world. They all neatly align with my general interest of looking at the ways that this tech is set to change the landscape — business and personal — around us, and how we navigate through it. But the use cases are also very specific.
Now, I’m shifting my focus to the broader landscape of digital transformation. I want to explore the ways that emerging tech beyond AI is set to transform how business fundamentally operates — because there are some big changes on the way. This is a phrase that has no doubt been repeated again and again over the last few decades, but the fact is that the tech underpinning business operations is evolving more rapidly than ever. This creates as much opportunity as it does uncertainty — a theme I will return to.
In order to take a comprehensive look, I have split this into a three-part series. In this post, I’ll take a broad, introductory view, and also look at the concept of the sentient enterprise. In the next post, I’ll explore the rise of emotionally-aware customer experiences, then finally I’ll look at the evolution of computing and wrap up the series.
For leaders tasked with charting a course through the complexities of the remainder of 2025 and 2026, this series offers a clear-eyed assessment of the challenges and opportunities coming our way. Enjoy the ride, and be sure to reach out if you have any questions about how we can support your digital transformation needs.
Digital Transformation Evolves Again
The business landscape is being reshaped by forces that demand more than iterative improvement.
The convergence of AI, advanced automation and ubiquitous data analytics is creating new operational paradigms. Customer and employee expectations are moving beyond mere convenience to demand deeply personalised, emotionally aware and frictionless interactions. In parallel to this, the foundational layers of tech and security are being challenged both by the force of geopolitical changes and by quantum computing, which creates opportunity while also posing major risks. In this dynamic context, simply keeping pace is a losing strategy. The gap between leaders and laggards will widen dramatically, not over decades, but in a matter of months.
So, what does leadership in this environment look like? It will be defined by the mastery of three interconnected domains that form the pillars of the future-ready business:
Sentience – This involves moving beyond basic automation to build an organisation that can sense, predict and act with increasing autonomy. It is the evolution from a business that uses intelligent tools to a business that is, in itself, an intelligent, responsive, dynamic organism.
Empathy – This pillar focuses on imagining customer and employee experiences that go beyond personalisation, they are contextually and emotionally aware. It requires engineering interactions built on a foundation of trust, transparency and inclusivity, recognising that these are hard-coded drivers of loyalty and revenue.
Resilience – This requires a focus on architecture and the underlying technological, security and energy infrastructure to both scale and withstand shocks. It is about building for a world where digital sovereignty is a strategic necessity and sustainable operations are a core business imperative.
The range of these three elements reach beyond mere trends. These are critical parts of the new landscape, and understanding how these moving pieces are set to evolve will put you in a position of growth and power.
The Sentient Enterprise
We are currently witnessing AI transitioning from a passive analytical tool to an active, autonomous agent of business value. The AI space is still rapidly evolving, and anyone who has had a conversation with a provider of AI-powered systems knows that value and pricing and ROI remain slippery concepts. But the tech itself is here, it is operational and it is changing how we operate. This shift is fundamentally reshaping enterprise ops, strategy and the very definition of a workforce.
Sentience is no longer the domain of science fiction; it is an emerging reality for organisations that are moving beyond simple AI adoption to a deep integration of intelligence into their core processes. This includes the rise of agentic AI to the symbiotic relationship between humans and machines, and the ultimate convergence toward a new form of "living intelligence”.
The Rise of the Digital Workforce
The initial frenzy surrounding generative AI – systems capable of creating content – is now maturing into something more operationally significant: the rise of Agentic AI. These are autonomous AI systems, or “agents”, that can plan, take action and even set their own intermediate goals to achieve a high-level outcome defined by a human user.
This represents a shift from AI as a “co-pilot” that assists humans to AI as a virtual worker capable of executing complex, multi-step tasks independently, with the ability to manage entire workflows. The potential applications span every business function, from predicting disaster recovery needs and initiating workflows, to dynamically adapting supply chains based on AI analysis. This activity is being supported by a burgeoning ecosystem of infrastructure, including specialised developer frameworks, multi-agent orchestration platforms and even agent-specific payment systems like Stripe Issuing, which allows developers to generate single-use virtual cards for agents to make authorised purchases.
This evolution from content generation to autonomous action introduces a new layer of complexity and risk that demands C-suite attention. The emergence of a digital workforce that can be “managed” — onboarded, assigned roles and measured for performance — is initially an operational and HR challenge. However, as these agents are granted greater autonomy, including budgets and the authority to transact on the company's behalf, the implications escalate significantly. Visions from major tech companies like Google and Amazon include agents that can handle tasks like booking travel or making purchases end-to-end. This raises profound questions of liability and governance. If an AI agent makes a catastrophic financial decision, enters into an unapproved contract or violates compliance regulations, who is accountable? This elevates the issue from a departmental concern to a critical corporate governance, legal and risk management imperative. Consequently, organisations must move swiftly to develop robust guardrails, authentication protocols and frameworks for auditing the decisions of these non-human actors to ensure their actions align with corporate intent, ethical standards and business objectives.
Real-World Applications in 2025-2026
Contrary to early fears of mass job displacement, the dominant narrative into 2026 and beyond is human-AI collaboration, not replacement. The central question leading organisations are asking is how to partner human expertise with AI capabilities to elevate overall performance and create value that neither could achieve alone. This is a pragmatic response to a clear business reality: the pace and complexity of modern business demands are outpacing human capacity — in Australia, we are seeing this tangibly occurring in the health space, where an ageing population is predicted to create demand we simply cannot meet with human resources alone. As such, technology investment is being viewed as a way to enhance human capabilities.
It is designed to absorb the mundane, repetitive and often frustrating tasks that drain productivity and morale — such as generating documentation, writing unit tests, provisioning software environments, screening resumes and so on — freeing human employees to focus on high-value activities like strategic thinking, creative problem-solving and building empathetic customer relationships. This partnership creates a powerful symbiosis where AI handles scale and computation, while humans provide judgment, context and creativity.
Some examples:
IT Operations and Cybersecurity: Agentic AI is being leveraged to respond in real-time to cyber attacks, providing a dynamic defence mechanism that outpaces manual intervention.
Financial Services: JPMorgan Chase's Contract Intelligence (COiN) platform exemplifies the power of applied AI. By using machine learning to interpret and extract key data from commercial credit agreements, the bank has reduced an annual workload of 360,000 hours of manual legal work to mere seconds, simultaneously reducing loan-servicing errors.
Customer Service: India's Axis Bank has deployed an AI-powered voice assistant, AXAA, which now handles 12-15% of all customer calls with a 90% accuracy rate. It operates 24/7, and provides support in multiple languages and dialects, significantly improving service efficiency.
This focus on augmentation extends to the internal workings of the organisation. The recognition that a poor internal experience directly hinders the ability to deliver a great external one is driving significant investment in initiatives to improve the employee-facing technology landscape. This includes creating role-specific dashboards that reduce cognitive load and decision fatigue, designing intuitive onboarding flows that nudge action rather than overwhelm with information, and even deploying systems that monitor behavioural signals (like rapid task switching or interaction sentiment) to provide early warnings of employee burnout.
The Pathway Forward
If anything, companies are hyper-focused on gen AI, overlooking how advanced capabilities will amplify its impact. This myopic view risks missing the larger transformation: the emergence of systems that do not just process data but actively sense, interpret and modify their environment in real-time. The ultimate goal of a modern digital transformation is to go beyond optimising the existing business by creating a business that is itself a responsive, evolving organism.
Companies that grasp this convergence early will build organisations that can perceive market shifts and adapt their operations dynamically, evolving their product and service offerings in real-time. The competitive advantage will result in the ability to learn and react faster than the competition. These early movers will establish data and capability advantages that FTSG predicts will become “nearly impossible for competitors to overcome”, fundamentally reshaping the competitive dynamics across every industry.
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