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Scooped by
JC Gaillard
onto Digital Transformation Leadership March 31, 1:44 AM
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How to control AI agent costs across tokens, infrastructure and ops before unpredictable workflows push spending past the value they deliver.
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Scaling agentic AI requires turning unstructured data into governed, reusable assets that systems can interpret and trust. Data leaders can start by building shared foundations and enforcing standards.
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From
www
While AI has generated remarkable successes in specific applications, the broader transformation many organizations expected remains elusive. Understanding why some companies thrive with AI while others struggle reveals crucial insights for leaders navigating this complex landscape.
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With the emergence of agentic AI, the picture changes significantly, requiring a rethinking of the very essence of the concept of a “business process”—from a static, predefined set of steps to a dynamic, adaptive, and intelligent AI-first system.
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From
www
Why is most AI producing almost nothing of value? The answer is less about the technology and more about how enterprises are deploying it.
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From
www
Enterprises deploying agents today can already meaningfully reduce risk by centralizing credential management, isolating execution environments and designing systems that explicitly account for prompt injection and model-driven attacks.
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Twelve themes separate companies that are truly rewired for AI from their peers.
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As organizations deploy artificial intelligence more widely, routine tasks are being automated, and some work is shifting from people to AI systems. Yet, many firms are finding that the returns on their investments in such systems are elusive.
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From
www
AI debt is an operational tax. What initially feels like momentum gradually reveals the cost over time with fragile releases, unpredictable performance, escalating maintenance costs and black-box systems.
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From
www
The old org chart is dying. Success now means learning to lead "agentic teammates" that handle the data grunt work so humans can focus on the big decisions.
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How to control AI agent costs across tokens, infrastructure and ops before unpredictable workflows push spending past the value they deliver.
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From
www
It is a striking paradox: Organizations are investing in AI at unprecedented levels, yet nearly 95% of AI pilots never reach production. AI is often described as a productivity accelerator. In practice, it quickly becomes a stress test, revealing how decisions are made, how authority works and whether the operating model can really handle AI.
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From
www
Transformation is coming for every organization, far faster and far more horizontally than any wave of technology that came before it.
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From
www
Many IT leaders are being asked to defend AI results they can’t explain, leading to some disappointment over vendor and platform choices.
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From
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Don't let early success blind you; if your AI's behavior is getting harder to explain, it is time to stop patching the old setup and fix the architecture.
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From
www
Poor governance and a lack of collaboration with suppliers and partners can lead to disaster
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From
www
Previous waves of digital transformation, like the arrival of computers, the internet and cloud, made it necessary to rebuild our technological foundations. And lots of organizations that didn’t realize this aren’t around today. Agentic AI has the potential to be as transformative as any of those, and just as likely to need a rethink from the ground up.
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CIOs have long struggled to balance enterprise tech budgets—and big investments in AI are compounding the problem. Our research shows how they can reallocate expenditures to generate maximum growth.
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From
www
Across industries, CEOs, CIOs and other enterprise leaders are having the same conversation and asking the same question: “We want to adopt AI. Where do we begin?” ; It’s an important question, but it’s not the first question most of you should ask. The first question should be, “Are we ready?”
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CIOs are facing unrealistic expectations. Here's what you need to do to make those digital improvements count in the next 18-24 months
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From
www
It's not the tech that's the problem, it's your business case, says Forrester
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From
www
Podcast hosts talk about $300-per-day agents, and AI experts say that figure is realistic if IT teams don’t put limits on their use.
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From
www
From the executive suite, transformation looks like progress. From the middle of the organization, it can feel like confusion and overload.
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From
www
Most AI projects stumble due to faults in the organization, not the models themselves. Leaders need to know when to fix and refocus an initiative internally, or when to kill it.
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From
www
IT strategy is shifting from one-off updates to managing six overlapping waves, like digital workforces and virtual simulations, that all need to work together.
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From
hbr
The question of who controls AI is the critical org-chart issue at the dawn of the AI era, and it will influence a company’s strategy, investment levels, and the distribution of power and influence among leaders. How can organizations decide?
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