New technology in the business situation
Build new capabilities by integrating AI into how your organisation works, makes decisions and structures teams, while preserving human judgement, keeping accountability clear and staying aligned with strategy.
Summary ideas
Keep the fundamentals aligned
AI success still depends on alignment between strategy, operating model, leadership, culture and people.
Consider the organisational impact
Explore how AI changes strategic position, work, decisions, coordination and the capabilities your organisation needs.
Choose your direction
Leaders must decide how to balance AI-driven efficiency with improvements to employee experience and organisational capability.
We began our discussion with the organisational performance model. It positions the operating model as the intermediary between business strategy and organisational performance. We explained that organisations are both social and technical in nature and that sustainable transformation requires leaders to jointly attend to both dimensions. We explored the required fit between business direction and all other complementary points of the star model. We emphasised collaborative design and collective ownership and the importance of engaging people in creating their future.
There is one topic, however, that is presently impossible to ignore in the business situation of every leader: AI. This technology dominates discussion and sells out events and conferences as leaders seek to understand how it will impact their business and competitiveness. Anyone who claims to know where the world of work and AI will lead us, is speaking with more certainty than the evidence allows. There is very limited data to suggest any predictability on the scale and impact AI will truly have in organisations. With that said, we can still look back and learn from other technologies that were new at the time and use that lens to attempt to look forward. In doing so, we work with heavy assumptions.
Improved performance is not guaranteed
Organisations have been implementing technologies and automating work for many decades. An important difference between AI and past technological advancements is that AI is the first technology that can directly participate in knowledge work, decision-making, coordination, creativity and learning. These elements were previously found exclusively in human capability. Herein lies a significant risk embedded in the dazzling possibility.
The introduction of new technology does not automatically translate into performance gains. Organisation researchers detailed this principle in early 1950s and codified it into a new ‘socio-technical’ understanding of work design. The formative study found the introduction of new mining technologies did not automatically translate into improved production. It had potential to degrade performance through fundamentally changed work activity and create issues such as the breakdown of autonomous work groups, the rise of managerial overhead, lost social cohesion and increased conflict. An important learning was that new technology, work design and social impact must all be considered and changed together.
CHOICE AND VOICE
Business direction and value-creating work
We have noted that design must begin with business direction and the value-creating work required to produce goods and services for a market. New technology has never changed this principle. Yet, many conversations about AI quickly orient to tools. This instrumental view leads to questions such as which tool/model should we use and where should we deploy it first? These are perhaps not the first questions we need to ask.
These broad questions sit at the intersection of strategy, business direction and customer expectations, technological capability, work redesign, unique human value and operating model coherence. The first instinct of most organisations is to graft technology into an existing operating model. In these scenarios, the technology will underdeliver its potential and may lead to decreased organisational performance.
Powerful questions
1. What new possibilities exist for our business direction with AI capability?
2. How can AI change and/or contribute to the work and decisions required to deliver today’s business direction?
3. What work activity and decisions can be handed over to AI? Where will AI support human capability? What activity must remain distinctly human?
4. How will AI, seen in its capability to do work and make decisions, be overseen for quality assurance?
5. What are the consequences of any of these possibilities to other design choices in the operating model understood as a connected whole?
considering ai
1. If expertise becomes more widely available, do decisions still need to move up the hierarchy as they have in the past?
2. If AI can monitor performance data and make real-time recommendations, do we need the same management or integrator jobs?
3. Who remains accountable for assurance and decision quality when AI becomes part of the workflow?
4. What capabilities must organisations build to verify, challenge and govern AI-generated recommendations?
redesigning workflows
Management
AI will change management work because management work is highly oriented to information processing to coordinate, forecast and convey information. Management activity has historically depended on specialist knowledge accumulated through career experience. These tasks will increasingly be performed by AI agents and/or people performing value-creating work in the value stream. This progression of technological capability understandably stirs up long-accepted views about managerial purpose and tasks.
The essential question is, how will the nature of management change? Relatedly and equally important is the career development benefit of managerial jobs. Nearly every organisation has developed its leadership pipeline through entry-level and junior jobs where employees learned to interpret information, solve problems and make decisions before progressing upwards through increasing levels of responsibility. If AI assumes a growing proportion of this work, the impact to succession planning is easy to see. We have seen case studies from the legal industry where legal AI took over most of the analysis and some decision-making work, stripping away the ranks of junior development jobs and the learning experience they represent.
The challenge is not simply adopting new technology. It is redesigning the operating model, work system and talent pipeline to ensure that decision quality, accountability and the development of future leaders remain strong in an AI-enabled organisation.
A note on the “AI-native” organisation
Throughout this guide, we have described an operating model as a collection of design choices that is organised around value-creating work and must be coherent. A useful thought experiment for a business leader to ask is:
If I were creating an organisation today, knowing AI exists, what would I design differently?
This is the essence of an AI-native organisation. It is designed around AI as a core provider of work activity and decisions. It is not an organisation that has plugged AI tools into existing activity to replace or augment human talent. It assumes AI is available when designing work as an integrated part of the value stream or management operating system. The AI Native organisation would not function if AI were removed. Therefore, AI is a fundamental part of the conversation from day one of the operating model design.
The most advanced applications of AI may paradoxically make organisations more human. There are known cases (IKEA, DBS and Telstra) where routine cognitive work has been allocated to AI without associated layoffs of human talent. Skills such as judgment, empathy, creativity, facilitation, negotiation, trust-building and collective sense-making become more valuable where humans were assigned to work activity and decisions deemed not replaceable by AI. We must further emphasise the trust-building point because it is essential in a growing landscape of misinformation and deep fake content. Truthfulness and trust will become one of the most important currencies going forward.
The leadership challenge
The leaders who create the most value from AI will not be those who deploy tools. They will be those who rethink what is possible, how value is created, how work is organised, how decisions are made, how the system is governed and how the operating model fits together to embrace the new technology. They will be the leaders who involve their organisation in the development of the future organisation. AI technology is an invitation to rethink and redesign the operating model itself.
SOURCES
- Mateer, W., Tolchinsky, P., & Turgoose, P. (2025). Déjà vu all over again: what the past can teach us about the future. Journal of Organization Design, 14(1), 15-22.
- Malone, T. W. (2018). Superminds: The surprising power of people and computers thinking together. Little, Brown Spark.
- Orlikowski, W. J. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398-427.
- Orlikowski, W. J. (2000). Using technology and constituting structures: A practice lens for studying technology in organizations. Organization Science, 11(4), 404-428.
- Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3-38.
- Worley, C. (2026, January 7). AI’s magic trick: Why executives should watch both hands. LinkedIn. https://www.linkedin.com/pulse/ais-magic-trick-chris-worley-zzgxc/