The first step is to identify the problems or opportunities that digital transformation can solve. This involves carefully assessing business processes and goals, asking questions such as: What inefficiencies need to be addressed? How can generative artificial intelligence (gen AI) improve the customer experience? Are there decision-making processes that could be improved with automation? These goals should be specific and measurable for effective evaluation and to ensure that the impact of AI technologies can be tracked.
Once they have identified the problems that need to be addressed, companies can translate them into goals. These could include improving operational efficiency by a certain percentage, improving customer response times, or increasing the accuracy of sales forecasts. Defining success metrics, such as accuracy, speed, cost reduction, or customer satisfaction, gives teams specific goals and helps avoid overreaching.
Across industries, the pattern is the same: AI is changing what companies do and how they do it. Yet a striking blind spot remains. 79% of executives say AI will contribute significantly to their revenue by 2030, but only 24% can clearly see where those revenues will come from. This gap between expectations and results represents the leadership challenge of this decade.
“By 2030, we will do things that were previously too expensive to be ROI-positive. We will also build products that simply couldn’t exist without AI semantic understanding.”
Alex Schultz
Vice President Analytics and Chief Marketing Officer, Meta
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