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Scooped by
JC Gaillard
onto Digital Transformation Leadership July 11, 2018 2:16 AM
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In the 21st century technology has become a ubiquitous part of modern workforces. Businesses are increasing their IT budgets and investing more in new IT designed to energise business performance and staff productivity. However, it seems not all employees feel quite so confident in their ability to use new technology at work
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Interestingly, it’s not usually the quality of the technology but misaligned goals, poor planning or unrealistic expectations that caused failure.
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As AI adoption accelerates, trust and security must become part of the foundation, not an afterthought.
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After a flood of AI experimentation, IT leaders are going back to the basics of governance, change management, and metrics to ensure initiatives deliver key value for the business at scale.
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Too many organisations are still operating as they go. Measuring the quality of agent behaviour is often ad hoc, based on gut feel rather than consistent benchmarks, which undermines trust and makes it incredibly difficult to prove value.
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While a large percentage of IT and business leaders believe their AI efforts will meet or exceed expectations, only a small number have successfully deployed projects thus far.
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From
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Companies are under pressure to pause digital innovation as costs rise and uncertainty grows—but holding back risks falling further behind in the age of AI and data-driven change. Research shows the most effective organizations avoid waste by funding projects incrementally based on evidence, pairing autonomous teams with shared resources, and continually reallocating talent and capital to initiatives with the greatest strategic impact. By adopting these habits, firms can double down on digital innovation while ensuring that every investment advances long-term business value.
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Most AI projects never scale. MIT's Paul McDonagh-Smith explains why culture, governance and leadership, not technology, decide who succeeds.
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