With generative AI expanding across industries, many organizations are adopting faster than they shouldt. This article highlights five common signs that your AI strategy may be misaligned or prematurely scaled, with practical insights on how to reset before it's too late. Read the article to reassess your roadmap and contact Lotus Beta Analytics to explore a strategy that builds value and avoids missteps.
What are the main strategies for implementing generative AI?
Researchers have identified four archetypes for implementing 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 with low-cost, high-impact solutions; and Strategic Builders, who take a long-term approach to develop generative AI for owning intellectual property and achieving sustained advantages.
Why do many generative AI initiatives struggle with ROI?
Many companies encounter difficulties in translating their ambitions into measurable impacts as they scale generative AI initiatives. Despite increasing adoption, a significant number of these initiatives fall short on return on investment (ROI), reflecting the complexities 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; Yash Raj Shrestha, an Assistant Professor at the University of Lausanne; Amit Joshi, a professor of AI and marketing strategy at IMD; and Michael Wade, a professor of strategy and digital transformation at IMD.
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