Many organizations are racing to implement GenAI without a coherent plan, and that can be a costly mistake. This article from Harvard Business Review outlines what separates forward-thinking GenAI strategies from the ones that stall or backfire. It offers practical questions to help leaders align GenAI with core business goals, avoid hype-driven decisions, and create value at scale. Read the article to pressure test your approach, then contact Tony Hunt Consulting for expert guidance on making your AI investments count.
What are the main strategies for implementing generative AI?
Researchers have identified four archetypes for how companies are strategically using generative AI: Bold Innovators, who aim to reshape their markets; Disciplined Integrators, who focus on trust, control, and compliance; Fast Followers, who seek quick wins through low-cost, high-impact solutions; and Strategic Builders, who take a long-term approach to develop generative AI for owning intellectual property and driving sustained advantages.
Why do many generative AI initiatives struggle with ROI?
Many companies face challenges in turning their ambitions into measurable impacts as they transition from generative AI pilots to scaled efforts. Despite increased adoption, a significant number of generative AI initiatives fall short on return on investment (ROI), highlighting the complexity and high-stakes nature of developing an effective generative AI strategy.
Who are the experts behind the research on generative AI strategies?
The research on generative AI strategies was conducted by a team of experts, including Konstantinos Trantopoulos, an advisor and research fellow specializing in strategy and organizational performance in the era of AI; Yash Raj Shrestha, an Assistant Professor and Group Head at the Applied Artificial Intelligence Lab; Amit Joshi, a professor of AI and marketing strategy; and Michael Wade, the TONOMUS professor of strategy and digital transformation.
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