The breathless pronouncements surrounding Artificial Intelligence often paint a picture of wholesale disruption, a technological tidal wave poised to obliterate established business practices. Yet the truth is more nuanced: AI does not replace strategy; it replaces bad strategy. In the absence of a coherent, adaptive, and intentional strategic framework, AI does not generate value, it magnifies inefficiency.
The Illusion of Technological Substitution
Many business leaders and business analysts approach AI with a sense of urgency, believing that rapid adoption equates to competitive advantage. This mindset fosters an arms race of AI investments, labs, data infrastructure, and talent, often without a clear strategic purpose. However, AI cannot compensate for a lack of strategic clarity, and it is here that business analysts have a crucial role to play: connecting operational realities with strategic intent. A retail company without a defined competitive edge cannot expect a recommendation engine to deliver meaningful differentiation. Similarly, a manufacturer lacking a coherent pricing model would not find salvation in predictive analytics. AI magnifies existing systems, rewarding firms with sound processes and coherent objectives, and penalizing those without them.
Real Value Emerges When Strategy Leads
AI creates real business value when it serves an intelligent strategy. The critical difference between leaders and laggards in AI adoption is strategic intent, not access to data or talent. Leading firms define precise use cases aligned with commercial objectives, and business analysts often frame these use cases and then deploy AI selectively to enhance those capabilities.
For instance, Amazon's recommendation engine, a successful example of AI in commerce, was built upon a clear understanding of its platform model and the need to increase customer retention and basket size. Similarly, UPS's use of route optimization algorithms stems from a well-defined strategy of logistics efficiency. In both cases, AI succeeded because it was directed at the right problem.
When strategic clarity precedes AI investment, the technology becomes a force multiplier. AI improves forecasting accuracy when the forecasting question is well-defined. It enhances personalization when the value proposition is clear. It enables automation where workflows are standardized and consistent with business goals. The returns are not just technical; they are strategic.
What Bad Strategy Looks Like in an AI World
Bad strategy, even when powered by advanced AI, remains bad. Common signs of misalignment include:
- AI for AI’s Sake: Implementing machine learning models or chatbots without a business case leads to projects lacking adoption and return on investment.
- Overemphasis on Tools: Focusing on acquiring platforms rather than solving specific problems, resulting in underutilized tech stacks and frustrated business units.
- Data Hoarding Without Intent: Amassing data lakes with no clear plan for analysis or usage, as AI thrives on relevant, structured data, not just quantity.
- Misplaced KPIs: Using AI to optimize narrow operational metrics while ignoring broader strategic outcomes.
These patterns often lead to pilot projects that never scale, unclear model outcomes, and frustrated stakeholders, problems that skilled business analysts are uniquely positioned to diagnose and prevent.
AI as a Strategic Diagnostic
Paradoxically, AI adoption can reveal more about an organization’s strategy than it solves. When a firm struggles to identify valuable AI use cases, that is often a symptom of broader strategic ambiguity. Where is the firm creating value? Who is its core customer? What decisions need to be made faster or more accurately? They are not engineering challenges, they are core questions for business analysts and strategic decision-makers.
In this sense, AI acts as a mirror, reflecting strengths and weaknesses in positioning, differentiation, and cross-functional alignment. Analysts can use this moment to drive enterprise-level insight, inform strategic pivots, and frame technology investments. Strategy in the Age of Algorithms
What does a sound strategy look like in an AI-enabled business?
First, it must be data-literate. Strategic leaders must understand what data exists, how it is governed, and where it can create advantage. This does not mean becoming technologists but making data a central consideration in strategic planning.
Second, strategy must be adaptive. AI models learn from feedback loops. The organizations that benefit most from AI are those that are agile enough to respond to those insights, whether reconfiguring supply chains, refining segmentation, or adjusting pricing dynamically.
Third, strategy must be ethically grounded. As AI systems begin to influence credit scoring, hiring, and content moderation, organizations must have a clear set of ethical principles. Values, not just data, must guide decisions. An AI system that reinforces bias or breaches trust can quickly destroy strategic goodwill built over decades.
Finally, strategy must be human-centered. While AI may automate tasks, strategic judgment, understanding context, nuance, and long-term consequences, remains the domain of humans. The best strategies define where AI adds value and where human insight remains essential.
Conclusion
AI is not a replacement for strategy; it is a referendum on it. In firms with a clear vision, coherent objectives, and operational discipline, AI accelerates value creation. In firms without those elements, AI adds cost, complexity, and noise.
Strategic leaders and business analysts must resist the allure of technological determinism and refocus on the fundamentals of competitive advantage. They must ask not what AI can do, but what the business needs and how AI can serve that agenda. In this way, AI becomes not a black box of complexity, but a mirror that reflects the quality of strategic thinking.
True digital leadership is not about adopting every emerging technology. It's about making technology serve strategy, not the other way around. In that equation, AI becomes not a threat or a panacea, but a powerful ally in the hands of those who know where they are going.
Author: Taiwo Shotunde
TAIWO SHOTUNDE is a finance and strategy professional with expertise spanning business strategy deployment, emerging technologies, technology governance, risk management, and regulatory compliance. Taiwo has worked with organisations such as KPMG, the United Nations Development Programme (UNDP), and the Oxford Creative Destruction Lab. An MBA graduate and Dean’s List awardee from the University of Oxford. Her work bridges finance, innovation, and governance and has contributed to high-impact initiatives across smart technologies and sustainable finance, bringing a structured, data-driven, and strategic lens to complex business challenges.
LinkedIn: Taiwo Shotund