Over the last year, we have met with many executive leaders who are struggling to come to terms with AI in their organisations: Voices and opinions abound, from the deeply cynical to wildly optimistic. AI is a transformative tool in the workplace, but many leaders are struggling to move beyond ChatGPT and Copilot. There is so much more to the story. So how can business leaders truly find value in leveraging AI to bring innovation and sustainable growth, not just deliver (as the apocryphal Henry Ford quote says) “faster horses”?
In a recent report (AI-Driven Methods for Cost-Efficiency, 2025), Gartner argues that most enterprise AI investments aimed at improving individual productivity deliver only limited short-term returns. Instead, they suggest that firms should pivot toward AI initiatives that enhance system-level efficiency—optimising working capital, renegotiating contracts, improving cash forecasting, and reducing service provider switching costs. These operational moves, Gartner claims, provide clearer and faster ROI than abstract productivity gains harvested one employee at a time.
It’s a compelling and pragmatic view, which we agree with. But is it the whole story?
Peer-reviewed research provides partial confirmation of this idea. Studies in management and organisational psychology consistently show that while individual productivity enhancements, such as wellness programs or better tools, can improve task-level performance, they do not reliably translate into significant firm-level gains unless they are integrated into broader systems or aligned with strategic intent.
Brynjolfsson and McAfee’s work on technological innovation highlights the “productivity paradox,” where firms invest heavily in technology but see inconsistent performance improvements. Moving beyond the “paradox” requires more than technology to drive productivity, but rather alignment and complementary innovation allow innovators to scale and gain a competitive edge.
The evidence also tells us that system-level optimisation is only one part of the opportunity. A growing body of high-quality research suggests that the real long-term value of AI lies not in shaving costs but in reshaping what a business does and how it decides. Strategic alignment and innovation are the game-changers.
AI, when applied to smart KPIs, scenario analysis, and decision-making frameworks, can strengthen strategic clarity and responsiveness. Over the medium term, this enables better capital allocation and value capture. And in the long term, AI’s most powerful use may be in fostering innovation and differentiation—enabling new business models, product development, and R&D acceleration.
This layered perspective suggests that AI should not be viewed as a single investment stream, but rather as a portfolio of investment options across three distinct horizons.
A Framework for AI Investment Decision-Making
| Time Horizon | Strategic Focus | AI Investment Class | Value Realised |
| Short Term | Cost reduction, efficiency | System-level automation, forecasting, optimisation | Immediate cash and operational savings |
| Mid Term | Strategic alignment, agility | AI for KPI transformation, scenario planning | Smarter decisions, better capital allocation |
| Long Term | Innovation, growth, differentiation | AI-enabled R&D, product innovation, new models | Competitive advantage, new revenue streams |
By organising AI initiatives into this kind of structured portfolio, executive teams can move beyond binary choices—between “save money” and “be visionary”—and instead make balanced, sequenced bets across cost, strategy, and growth.
So yes, Gartner is right: system-level efficiency is where the quick wins lie. But the enduring gains will come from using AI to think differently, act strategically, and innovate boldly.
As a CIO, you have the unique opportunity to lead your organisation into the future by leveraging AI not just for cost efficiency but for strategic innovation and growth. It’s time to rethink your AI investments and align them with your long-term business goals. Start by evaluating your current AI initiatives and identifying areas where AI can drive strategic clarity, responsiveness, and innovation. Collaborate with your executive team to create a balanced portfolio of AI investments that spans cost reduction, strategic alignment, and growth. Together, let’s unlock the full potential of AI and transform our businesses for the better.
If you would like to discuss how we can assist you, please don’t hesitate to contact us.
Authors:
Daniel Thomas PhD, Duncan Unwin
Daniel Thomas leads AI thought leadership in the Digital & ICT Advisory Practice. Based in Melbourne, his PhD research focused on AI and artificial agents. Duncan Unwin leads the Practice, with research interests centred on the economic and performance effects of technology investments.
References
Gartner Report
Howard, C., Suda, N. and Sribar, V., 2025. AI-Driven Methods for Cost-Efficiency. Gartner, Inc. Document ID: 6411475. [online] Available at: https://www.gartner.com/en/documents/6411475 [Accessed 30 Jul. 2025].
Keding, C., 2021. Understanding the interplay of artificial intelligence and strategic management: four decades of research in review. Management Review Quarterly, 71(1), pp.91–131. Available at: https://link.springer.com/article/10.1007/s11301-020-00181-x [Accessed 30 Jul. 2025].
McAfee, A. & Brynjolfsson, Erik. 2008. Investing in the IT that Makes a Competitive Difference. Harvard Business Review. 86. 98-107.
Brynjolfsson, E., Benzell, S., & Rock, D. 2020. Understanding and addressing the modern productivity paradox. Massachusetts Institute of Technology.
van de Wetering, R., Mikalef, P. and Pateli, A., 2021. Strategic alignment between IT flexibility and dynamic capabilities: an empirical investigation. arXiv preprint. Available at: https://arxiv.org/abs/2105.08429 [Accessed 30 Jul. 2025].
Spaniol, M.J. and Rowland, N.J., 2023. AI-assisted scenario generation for strategic planning. Futures & Foresight Science, [online] Available at: https://forskning.ruc.dk/en/publications/ai-assisted-scenario-generation-for-strategic-planning [Accessed 30 Jul. 2025].
Csaszar, F.A., Ketkar, H. and Kim, H.J., 2024. Artificial Intelligence and Strategic Decision-Making: Evidence from Entrepreneurs and Investors. arXiv preprint. Available at: https://arxiv.org/abs/2408.08811 [Accessed 30 Jul. 2025].
Kiron, D., Schrage, M., Candelon, F., Khodabandeh, S. and Chu, M., 2024. The Future of Strategic Measurement: Enhancing KPIs With AI. MIT Sloan Management Review / BCG. Available at: https://sloanreview.mit.edu/projects/the-future-of-strategic-measurement-enhancing-kpis-with-ai [Accessed 30 Jul. 2025].