70% of leaders cite speed as new strategy as AI reshapes work: Deloitte report

Nearly 70% of business leaders say their primary competitive strategy over the next three years is to become fast and nimble, enabling their organisations to quickly adapt to shifting markets, customer expectations, and technological disruption. 

The finding from the 2026 Global Human Capital Trends survey reflects a growing realisation among executives that the traditional pace of organisational change may no longer be viable in a world shaped by artificial intelligence, economic volatility, and an evolving workforce.

The report suggest that organisations are no longer merely balancing competing workplace priorities such as control versus empowerment or automation versus augmentation. Instead, many are approaching a tipping point where the speed and scale of transformation are fundamentally altering how work is designed, executed, and led.

At the center of this shift is a phenomenon long used to describe business evolution: the S-curve of growth, the report noted. Traditionally, organisations experience gradual progress followed by rapid acceleration before reaching a plateau. Today, however, that curve is compressing.

Advances in AI and workforce transformation are accelerating growth cycles and bringing maturity points much sooner, forcing companies to leap to the next curve faster than before to remain competitive.

In practical terms, this means that long planning cycles and predictable execution models may struggle to keep pace with a world where technologies, customer demands, and workforce expectations evolve in real time. Increasingly, success depends on an organisation’s ability to sense change early, experiment rapidly, and adapt continuously.

Ironically, while technology is driving much of this disruption, it may no longer be the main source of competitive advantage. AI capabilities are becoming widely accessible, making technological differentiation harder to sustain. Instead, the research points to a different edge, human capability.

Qualities such as creativity, judgment, adaptability, and the ability to navigate uncertainty are emerging as the factors that distinguish high-performing organisations. The real value of AI, researchers argue, lies not simply in deploying the technology but in reimagining work so that humans and machines operate in concert.

Yet many organisations are still approaching AI primarily as a technology investment rather than a transformation of work itself. According to the research, 59% of organisations currently take a tech-first approach to AI adoption. Those companies are 1.6 times more likely to fall short of expected returns on their AI investments compared with organisations that prioritise human-centered redesign of roles, workflows, and decision-making.

The difference highlights a growing realisation among executives: technology may enable change, but people determine whether that change creates value.

Three tipping points shaping the future of work

The research identifies three major tipping points that are beginning to reshape how organisations operate. 

The first involves the evolving relationship between humans and machines. As AI becomes embedded in everyday workflows, companies are moving beyond a model where humans and machines simply work alongside each other. Instead, they are exploring integrated human–machine collaboration, raising questions about decision rights, accountability, and trust in algorithmic outputs.

The second tipping point concerns how organisations define success. For years, many businesses have focused on efficiency and cost reduction. But as talent shortages intensify and innovation becomes critical to growth, leaders are beginning to shift from cost efficiency toward value creation, reinvesting productivity gains into new capabilities and human potential.

The third tipping point reflects the collapse of rigid organisational structures. Traditional jobs and functions are increasingly giving way to dynamic orchestration, where skills, data, and technology are deployed in real time to address changing business needs. In this model, learning and reinvention become continuous rather than episodic.

Trust, culture, and the AI workplace

The report notes that alongside these structural shifts, organisations are grappling with deeper questions about trust and culture in an AI-powered workplace.

As algorithms increasingly generate insights, recommendations, and content, questions about authorship, accuracy, and bias are intensifying. Some organisations are beginning to expand their focus from traditional cybersecurity to what researchers describe as “disinformation security,” ensuring that the data and AI outputs guiding decisions remain reliable.

At the same time, the growing presence of intelligent systems is subtly reshaping workplace culture. Workers are beginning to question what constitutes effort, ownership, and fairness when machines contribute to outcomes. 

Without deliberate leadership, these uncertainties can accumulate into what experts call “cultural debt,” gradually eroding trust within organisations.

Reinvention becomes the baseline

Perhaps the most striking implication of the research is that transformation itself is changing. Reinvention is no longer an occasional response to disruption, it is becoming the default operating condition for organisations.

Innovation, scaling, and efficiency, once sequential phases of growth, must now occur simultaneously. Teams are expected to experiment, deliver results, and optimise performance at the same time.

In this environment, the organisations most likely to thrive may not be those that simply deploy the most advanced technologies. Instead, they will be those that intentionally cultivate what researchers describe as a “human advantage”, a workforce capable of learning continuously, collaborating with intelligent systems, and reinventing itself as conditions change.