Fortune | FORTUNE 前天 20:55
AI投资巨大回报甚微,关键在于领导力而非技术
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尽管企业在人工智能领域投入了巨额资金,但大多数公司仍无法展示切实的业务成果。技术本身并非问题,员工也正在使用AI,但领导者在推动变革时缺乏必要的支持和准备,导致AI成为“沉淀资本”。研究表明,高达95%的生成式AI试点项目以失败告终,投资巨大却回报甚微。文章指出,变革的难点不在于技术,而在于人的因素。许多领导者在缺乏清晰指导的情况下被要求推动AI转型,并因害怕失败而不敢冒险。成功的企业则同时投资于技术培训和领导力发展,赋能领导者应对恐惧、阻力,创造战略清晰度,并为实验和失败提供安全空间。根本上,AI转型是领导力容量问题,而非技术问题,解决这一领导力缺口是实现AI投资回报的关键。

💰 **巨额AI投资面临回报困境**: 文章指出,企业已在人工智能领域投入了数千亿美元,但绝大多数公司未能实现显著的业务成果。MIT的研究显示,高达95%的生成式AI试点项目以失败告终,Bain报告称去年在生成式AI上的支出达300-400亿美元,而McKinsey则发现不到1%的公司认为其AI采用已“成熟”。这种巨大的投资与微乎其微的回报形成了鲜明对比,突显了当前AI落地策略的普遍性问题。

🧭 **领导力是AI成功的关键,而非技术**: 文章的核心论点是,AI转型的成败关键在于领导力的发展,而非单纯的技术难题。作者以其在Salesforce的经验为例,强调了变革的“人性化”方面决定了其成功与否。许多领导者在面对AI转型时感到迷茫和压力,因为他们被要求在不确定性中做出决策,并可能因失败而受到惩罚。成功的企业则认识到,需要同时培养领导者的技术能力和转型领导力,使其能够应对恐惧、建立信任、创造战略清晰度并鼓励实验。

💡 **解决领导力缺口,实现AI投资价值**: 文章强调,企业当前普遍存在“资金投入错误”,将AI视为技术问题而非领导力容量问题。成功的企业通过为领导者提供个性化支持,帮助他们处理复杂的对话(如员工对失业的担忧)、建立心理安全感以及应对阻力。这种对领导力基础设施的投资,能够帮助企业在AI时代建立持久的竞争力,将“沉淀资本”转化为实际回报,并构建超越技术的领导力优势。

Corporate America has already poured tens of billions into AI. Most companies can’t point to a single business result.

The technology works. Employees are using it. What doesn’t work is that we’re asking leaders to drive massive change without equipping them to do it successfully. Until that gap closes, AI will remain stranded capital.

The math is brutal. MIT found that 95% of generative AI pilots at companies are failing. Bain reports organizations spent $30 to $40 billion on generative AI in the past year. And McKinsey found fewer than 1% of companies describe their AI adoption as “mature.” Massive investment, negligible return.

I spent nine years at Salesforce leading through major transformations. The technical side of change is never the hardest part. It’s always the human side that determines whether things succeed or fail.

What nobody’s saying out loud

I keep hearing the same pattern in conversations with executives. They have AI mandates from the top, with no clarity on how to get their people ready, on top of everything else they’re already managing. And there’s this thing they’ll only say in private, “I don’t know what I’m doing.” Nobody does.

In most organizations, leaders are still rewarded for looking certain, staying in control, running tight systems. Take a risk with AI and get it wrong? Most people believe they’ll be punished for failure. Those same behaviors crush the experimentation and trust AI depends on. 

Companies are essentially handing leaders technical training and telling them to figure it out. That’s hope, not strategy.

When Bret Taylor became Salesforce’s Chief Product Officer, I got 30 minutes with him as a rising product leader. I knew our approach wasn’t working and spoke from the heart about what I was seeing and how it needed to be better. He could have dismissed it, as I was several levels down. Instead, he listened. 

We created an Associate Product Manager program that taught not just technical skills but also critical leadership skills like how to challenge the status quo, navigate conflict, work across teams, and show up under pressure.

We didn’t just mandate change or add a training program. We changed the nature of the conversations teams were having by injecting new thinking and new ways of working at a grassroots level. Then we listened closely to what was working and what was standing in our way and iterated on our approach in real time. That’s how you build lasting change, not by announcing something and hoping everyone figures it out.

Most companies are doing exactly that with AI. Funding tools and training, while neglecting the systemic change needed to drive real transformation.

What the 5% actually do differently

Harvard Business Review analyzed what separates companies where AI pilots succeed from the 95% where they fail. The differentiator isn’t the technology. It’s leadership.

The winning companies do two things at once. They fund technical training and fund developing leadership capacity for transformation. Their leaders can navigate fear and resistance across teams. They create strategic clarity and alignment. They create safety for experimentation and failure. They model risk-taking in uncertainty and hold people accountable to entirely new standards.

That requires real support. Not just workshops, but individualized help for challenging situations. How to have conversations about readiness. How to create psychological safety when someone says they’re afraid of being replaced. How to navigate resistance when it inevitably shows up.

Most companies lack that leadership infrastructure. Gartner found 66% of CEOs say their executive teams lack AI confidence. The leaders who can create clarity and safety in chaos, their teams will become AI-first. The ones who can’t? Their teams will just be busy.

You can’t solve an adaptive challenge with a training program. Leaders need help applying AI to their actual work: their specific role, team, challenges. They need a place to work through fear and uncertainty without career risk. That’s fundamentally different from what most companies are funding, and the 95% failure rate proves it.

Companies are funding the wrong intervention

Companies are treating AI as a technical problem when it’s a leadership capacity problem. Your competitors are making the same calculation right now. Some of them are getting different answers.

AI is forcing us to confront something we should have fixed years ago. We’re asking leaders to navigate unprecedented complexity with the same development approach that hasn’t worked for decades.

The companies that get this right won’t just succeed with AI. They’ll build leadership capacity that outlasts whatever technology comes next.

The billions are already spent. The question is whether they turn into returns or stranded capital. That answer depends entirely on whether you’re willing to fund the leadership gap, not just the technology gap.

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AI投资 领导力 企业转型 AI落地 人工智能 AI adoption Leadership Digital Transformation AI implementation
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