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How to Overcome Innovation FOMO & Use AI/GenAI to Solve Specific Business Problems
- Corporate leadership teams express the need to use AI and GenAI in operations, but it is important to remember that innovation is a process and must be matched to specific needs with evaluated risk and tied to measurable business outcomes.
- To maximize ROI in an enterprise-wide AI ecosystem, a slow and focused approach should be used to encourage a test-and-learn mindset. Transportation industries use AI for demand forecasting, inventory management, predictive maintenance, and route optimization among other applications.
- GenAI creates realistic messages, preserving brand reputation, and helps to communicate in ways that feel genuine. Retail industries use AI to analyze customer data and give personalized experiences and predict future behavior for targeting sales efforts and customer acquisition.
- In industries like healthcare and financial services, security concerns cause slower AI adoption, but AI enjoys a net positive impact in fraud detection as algorithms can identify anomalies. Fraud detection is a growing problem in finance.
- Banking industries use AI and machine learning to train modules with historical data, predict future cash flow, reduce version control issues, and gain better insight into current and future cash positions. AI is helping empower investors, especially those focused on sustainability.
- Leadership needs to ensure that change is a team sport, any new technology introduced must have measurable business outcomes, and that speed must be balanced with direction to maintain meaningful impact.
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