"US researchers that analysed hundreds of enterprise level generative AI tools found only one in 20 actually delivered significant value, despite big businesses pouring more than $60 billion into the technology." With much of the recent "productivity" conversation framing AI governance and regulation efforts as merely as a handbrake on progress and other "guaranteed" upsides, this piece by Joseph Brookes highlights that blind faith AI adoption is equally counterproductive and inefficient. Taking a more responsible approach to AI is largely about paving the way to more success and positive impact with AI implementations (and less re-work and backtracking) - happily, some of the clients we're working with on AI risk and governance see it exactly this way. Please reach out if you'd like to discuss more. https://lnkd.in/g3eFrNnT
"Only 5% of AI tools deliver value, says US study"
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AI Adoption Expert | Fmr. MIT AI Co-Chair | Helping Leaders Execute 10x Faster | ex-Red Bull, -Arterys (acq. by Tempus AI, NASDAQ:TEM), -ARPA-H AI Advisor
The real AI challenges are more "people & process" than technology. IME AI experiments "fail" because they're designed around existing hierarchical structures, and executive sponsors are (understandably) generally unwilling to rock the corporate boat; once you've got a "10x process improvement quick win," the logical next step is to zoom out and reengineer the organization's fundamental CX/organizational structure/workers' economic incentives—legacy implementations, which include entire departments with specialized bureaucratic functions, are rarely fit for purpose in this new context. Until there's enough pain to drive fundamental organizational change, we'll keep seeing expensive AI theater instead of transformation. The technology demands flatter, more agile structures between executive decision-making and customer interaction; most (but not all!) enterprises are not quite ready to confront the particulars that get you from here to there. (Above is my $0.02; Harvard Business Review article, linked, resonated with my own firsthand experience—and with what I've heard from other credible applied AI practitioners—and is worth reading in its entirety.) https://lnkd.in/eke28jMC
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Associate CIO | IT Gov. | AI & Data Gov. | Strategic Planning | Enterprise Architecture | Cybersecurity and Risk Management | Contract Negotiations | DR & BC | Identity Management | Capital Budgeting | Data Warehouse
This would measure the maturity of IT governance, organizational culture, innovation appetite and if IT is a strategic partner or just service delivery.
AI Adoption Expert | Fmr. MIT AI Co-Chair | Helping Leaders Execute 10x Faster | ex-Red Bull, -Arterys (acq. by Tempus AI, NASDAQ:TEM), -ARPA-H AI Advisor
The real AI challenges are more "people & process" than technology. IME AI experiments "fail" because they're designed around existing hierarchical structures, and executive sponsors are (understandably) generally unwilling to rock the corporate boat; once you've got a "10x process improvement quick win," the logical next step is to zoom out and reengineer the organization's fundamental CX/organizational structure/workers' economic incentives—legacy implementations, which include entire departments with specialized bureaucratic functions, are rarely fit for purpose in this new context. Until there's enough pain to drive fundamental organizational change, we'll keep seeing expensive AI theater instead of transformation. The technology demands flatter, more agile structures between executive decision-making and customer interaction; most (but not all!) enterprises are not quite ready to confront the particulars that get you from here to there. (Above is my $0.02; Harvard Business Review article, linked, resonated with my own firsthand experience—and with what I've heard from other credible applied AI practitioners—and is worth reading in its entirety.) https://lnkd.in/eke28jMC
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Marketing + Communications Leader delivering fractional CMO + CCO leadership to non-profits, tech startups and small to medium-sized businesses.
Great snippet: “The real opportunity—the one that will actually generate returns—is to look carefully at your internal operations and the external customer journey and start with how you can create real value, in the near term, using AI tools.”
AI Adoption Expert | Fmr. MIT AI Co-Chair | Helping Leaders Execute 10x Faster | ex-Red Bull, -Arterys (acq. by Tempus AI, NASDAQ:TEM), -ARPA-H AI Advisor
The real AI challenges are more "people & process" than technology. IME AI experiments "fail" because they're designed around existing hierarchical structures, and executive sponsors are (understandably) generally unwilling to rock the corporate boat; once you've got a "10x process improvement quick win," the logical next step is to zoom out and reengineer the organization's fundamental CX/organizational structure/workers' economic incentives—legacy implementations, which include entire departments with specialized bureaucratic functions, are rarely fit for purpose in this new context. Until there's enough pain to drive fundamental organizational change, we'll keep seeing expensive AI theater instead of transformation. The technology demands flatter, more agile structures between executive decision-making and customer interaction; most (but not all!) enterprises are not quite ready to confront the particulars that get you from here to there. (Above is my $0.02; Harvard Business Review article, linked, resonated with my own firsthand experience—and with what I've heard from other credible applied AI practitioners—and is worth reading in its entirety.) https://lnkd.in/eke28jMC
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“…The technology demands flatter, more agile structures between executive decision-making and customer interaction; most (but not all!) enterprises are not quite ready to confront the particulars that get you from here to there…” Christian Ulstrup #ai #management #digitaltransformation
AI Adoption Expert | Fmr. MIT AI Co-Chair | Helping Leaders Execute 10x Faster | ex-Red Bull, -Arterys (acq. by Tempus AI, NASDAQ:TEM), -ARPA-H AI Advisor
The real AI challenges are more "people & process" than technology. IME AI experiments "fail" because they're designed around existing hierarchical structures, and executive sponsors are (understandably) generally unwilling to rock the corporate boat; once you've got a "10x process improvement quick win," the logical next step is to zoom out and reengineer the organization's fundamental CX/organizational structure/workers' economic incentives—legacy implementations, which include entire departments with specialized bureaucratic functions, are rarely fit for purpose in this new context. Until there's enough pain to drive fundamental organizational change, we'll keep seeing expensive AI theater instead of transformation. The technology demands flatter, more agile structures between executive decision-making and customer interaction; most (but not all!) enterprises are not quite ready to confront the particulars that get you from here to there. (Above is my $0.02; Harvard Business Review article, linked, resonated with my own firsthand experience—and with what I've heard from other credible applied AI practitioners—and is worth reading in its entirety.) https://lnkd.in/eke28jMC
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Global Solutions Development & Operations Leader | Enterprise Governance and Vendor Management
You can't spell topic du jour without AI (wait - is that right?) AI is everywhere, and like any breakthrough technology, the promise and hype are easy to talk about. But once you dig in, the real story is in the challenge of adopting and integrating it into your business. That’s where solid data helps. The latest State of Enterprise AI Adoption report from ISG highlights those challenges — and, more importantly, how to avoid them so organizations can unlock AI’s value faster. https://lnkd.in/eBMEYETb
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The enterprise AI opportunity is enormous—but takes more than just technology. As our CEO, Kaveh Rostampor, says: "Deploying AI requires a combination of tools and knowledge, and we're in a great position to help here." This approach became the foundation of our AI Deployment Program (ADP): our specialized AI services arm designed to help you deploy AI for meaningful commercial outcomes, with a team of forward deployed business specialists and engineers. Discover more: https://lnkd.in/ew7X43Kt
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Account Executive at Whitefriar | Executive Online Reputation Management | Building a Strong Online Presence for Executives & Companies
“Think more AI experiments equals more value? Not if they're scattered and aimless.” A new MIT Media Lab report shows 95% of generative-AI investments deliver zero returns. Avoid repeating digital-transformation mistakes: focus AI pilots on core customer needs, keep them low-cost and scalable, and empower agile “ninja” teams. How can your next AI initiative drive real value? #AIExperimentation #DigitalTransformation #SmartInnovation Read more: https://lnkd.in/epKfqcjH
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95% of AI projects are failing! https://lnkd.in/eEiXCteC It’s not because the technology isn’t ready. It's because the business case isn't clear. A lack of purpose is the number one reason these projects fall flat. Find out how a strong "why" is the key to success. Watch our full discussion here: https://lnkd.in/grEnwrh6
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The Tech Startup CMO. Read my blog about tech, startups and marketing. For ambitious tech founders and marketing professionals excited to grow their business faster. Link to the blog in Contact Information:
Why 95% of Enterprise AI Investments Fail The tech industry is full of hype – and nowhere is this truer than with AI. The latest MIT report is an eye opener. In this blog we reveal: ✅ What the MIT report says ✅ Why 95% of generative AI investments fail ✅ How AI mirrors other enterprise deployments ✅ Examples where AI is delivering tangible value ✅ Why business process integration and ROI alignment are critical 👉 Read it here: https://lnkd.in/ewxMv3n6 #ArtificialIntelligence #EnterpriseAI #GenerativeAI #TechStrategy #DigitalTransformation #AIInvestments #MITResearch #AIinBusiness #TechMarketing #BusinessStrategy
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