Recent survey findings indicate that while many companies are racing to embrace artificial intelligence (AI), a significant number lack the necessary organisational framework, insights, and strategies to translate this adoption into substantial progress.
This underscores a critical issue in the business technology sector: the disparity between AI excitement and practical application.
Artificial intelligence, a concept that has been developing for decades, refers to the capability of a machine to imitate intelligent human behaviour.
It covers areas such as machine learning, natural language processing, and robotics. Many organisations see AI as a way to enhance productivity, improve decision-making, and gain a competitive edge.
However, without a clear strategy and robust structure, the transition from AI adoption to meaningful impact remains elusive.
This gap between ambition and execution is particularly pronounced among mid-sized enterprises and traditional industries, where legacy systems and siloed data architectures hinder seamless AI integration.
Even in tech-forward firms, a lack of cross-functional collaboration can stifle the effectiveness of AI initiatives.
Success in deploying AI at scale often hinges less on technical capability and more on organisational readiness, such as clear governance, talent alignment, and change management processes that encourage iterative learning and adaptation.
Another challenge lies in the measurement of AI outcomes. Many companies struggle to define what success looks like beyond cost savings or automation metrics.
To derive real value, organisations must shift their focus towards long-term capabilities like predictive accuracy, personalisation, and process optimisation.
This requires embedding AI into core business workflows, supported by continuous feedback loops and ethical oversight.
Without this foundational clarity, the risk of investing heavily in underperforming pilots or fragmented tools increases, undermining both confidence and ROI in AI ventures.
Key Survey Findings
- AI Adoption Is Rising Rapidly:
- 78% of organizations report using AI in at least one business function, up from 72% in early 2024 and 55% a year earlier (McKinsey Global Survey on AI, March 2025).
- 71% of organizations now regularly use generative AI in at least one business function, up from 65% in early 2024 (McKinsey Global Survey on AI, March 2025).
- Most organizations now use AI in an average of three business functions, but this remains a minority of all possible functions (McKinsey Global Survey on AI, March 2025).
- Framework and Strategy Gaps:
- Despite high adoption, many companies lack clear AI strategies and robust frameworks to translate adoption into measurable progress (McKinsey Global Survey on AI, March 2025).
- The gap is especially pronounced in mid-sized enterprises and traditional industries, where legacy systems and siloed data hinder seamless AI integration.
- Business Value and Challenges:
- Organizations deploying gen AI report notable cost reductions and revenue increases, particularly in customer service, healthcare, and finance (McKinsey Global Survey on AI, March 2025).
- 44% of organizations have experienced negative consequences from gen AI, including inaccuracy, cybersecurity, and explainability concerns (McKinsey Global Survey on AI, March 2025).
- Future Expectations:
- Three-quarters of respondents anticipate substantial or disruptive changes in their industries due to AI in the next three years (McKinsey Global Survey on AI, March 2025).
References and Survey Link
- McKinsey & Company: The State of AI – Global Survey 2025 (Full Survey)
- McKinsey: The State of AI in Early 2024
- Purdue: What Businesses Can Learn from McKinsey’s 2024 Global Survey on AI Adoption
- LinkedIn: State of AI in 2024; McKinsey survey reveals key insights