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Scooped by
JC Gaillard
onto Digital Transformation Leadership September 22, 1:43 AM
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Scoop.it!
Artificial Intelligence is not a strategy, a tool, or a trend. It’s a threshold.
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Scoop.it!
From
hbr
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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Why Technical Debt Has Become CIOs' Biggest Innovation Roadblock
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Urgency alone isn’t enough—without cultural alignment, strong governance and a clear purpose, digital transformation rarely delivers lasting results.
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From
www
Stuck in AI pilot purgatory? The real win is focusing on business problems, not hype, and scaling smartly with the right mix of tools.
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From
www
Past digital transformation struggles can offer valuable lessons to develop more effective strategies for AI implementation.
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Artificial Intelligence is not a strategy, a tool, or a trend. It’s a threshold.
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From
hbr
While companies have been “unbundling” their operations and outsourcing tasks for decades, advances in IT are now helping them take that strategy to a whole new level.
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The question isn't whether to invest in AI, but how to ensure those investments translate into measurable, real-world payoff.
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Today’s CIO must be more than a tech steward. Innovation and business alignment define the modern CIO’s role in driving growth.
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From
martech
AI at scale succeeds when teams are ready first. Build curiosity, clarify roles and redesign workflows before expanding technology.
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From
www
The flood of organizational requests for AI requires a strategic and structured approach driven by dedicated teams tightly aligned with business requirements.
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From
www
Balancing AI, Cloud, Digital Trust to Turn Disruptions Into Enterprise Opportunity
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From
technative
The competition to turn artificial intelligence (AI) into business value is heating up, but business leaders need the right tools to make AI deliver
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We’re on the cusp of a new software-enabled business model that will determine winners and losers in the coming decades. We call this service-as-software. Specifically, we believe enterprises will begin to organize knowledge work in new ways that harmonize islands of automation into a build-to-order assembly line for knowledge work.
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Just as earlier migrations were guided by stars or landmarks, this migration requires us to create our own compasses. These are not technical specifications but ethical bearings, meant to keep institutions human, even as cognition itself diffuses into every tool and transaction.
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From
www
Cost overruns, delays, and high failure rates have long been accepted as the price of innovation. But with a co-ambidexterous approach, CEOs can help their companies innovate smarter and faster.
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From
www
Digitizing processes can feel like a leap into the unknown for employees. The obligation of CIOs, as committed advocates for change, is to prioritize investment in training, change management, and mentoring colleagues during transformation.
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From
www
Strong influence across the company and leadership ranks takes years to build. It can vanish in the blink of an eye.
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From
www
95% of Enterprise AI Stuck in Pilot Purgatory: How Do the Rest Succeed?
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Too many companies are rushing to embrace the latest agentic AI innovations without considering the part played by best practice and governance structures.
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From
www
With AI and, in particular, agentic AI now in the mix, the conversation on where to deploy your AI isn’t cut and dried.
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From
www
AI is already spurring CIOs to rethink how they run IT departments, invest in technology platforms, and digitally transform businesses. But a clear-eyed view of IT’s future remains elusive.
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From
hbr
Leaders are repeating the mistakes of the digital transformation era by funding scattered pilots that don’t connect to real business value. The takeaway is not that AI experimentation is broken, but that it must be disciplined
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Ultimately, model makers and enterprises are focusing on the wrong issue: They should be computing smarter, not harder.
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From
the-cfo
Why AI is turning cloud spend into a board-level concern, and why CFOs must now own the economics behind every compute decision.
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