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Marketing AI Institute· Cathy McPhillips·· 2026-09-21AI 评分39

Pam Boiros 将在 MAICON 2026 谈 AI 适应为何比铺开工具更难

Why AI Adaptation, Not Adoption, Is the Real Work Ahead

文章要点
  • 1Pam Boiros 将在 MAICON 2026 演讲,讲 AI 落地与适应之间的人员侧差距
  • 2她的标准是当 AI 不再是独立项目、开始改变工作本身如何完成时,才算适应
  • 3她提出技能、工作流、护栏、衡量、文化五块积木,称文化最被团队低估
  • 4三年培训经验显示抵触根源是对角色与职业的恐惧,她判断仅靠更多培训不够
决策要点

AI 落地的真正分野不在工具铺开,而在工作方式是否随之重设计,文化与心理安全是最常被漏掉的变量。

  • 影响:培训场次和工具开通数衡量不了落地程度;重设计工作流、设好护栏的团队才可能把工具变成团队能力;把抵触只当培训缺口,预算可能花错地方。
  • 参考:可考虑先盘点团队哪些工作流真正围绕人与 AI 分工做了重设计;值得为员工留出受保护的实验时间,并让管理者公开分享自己的使用与教训。
  • 依据:五块积木框架与抵触观察来自讲者 Boiros 三年营销团队培训经验,经主办方宣传稿转述,尚无独立验证。
正文

Most marketing teams have rolled out AI tools. Far fewer have changed how they work with them in their jobs.

The gap between adoption and adaptation is what Pam Boiros will address at MAICON 2026 in her session, "AI Adaptation: The People Side of Scale."

Boiros is a fractional Chief Marketing Officer at Bridge Marketing Advisors and an AI strategist who has led marketing organizations at companies including Skillsoft and meQuilibrium. She is also the co-founder of Women Applying AI, a global community focused on helping women build practical, hands-on AI skills.

Adaptation Is a Different Way of Working

For leaders who feel they've already done the hard part by rolling out AI tools, Boiros draws a sharp line between what's been accomplished and what still lies ahead.

"You know you've moved from AI adoption to AI adaptation when AI stops feeling like a separate initiative and starts changing how the work itself gets done," Boiros says.

Adoption is relatively easy to spot: people have access to tools, attend training, and individual use cases start to surface. Adaptation looks different. Teams begin redesigning workflows around what humans and AI each do best. Managers coach AI-assisted work and set expectations for quality. People have enough confidence to experiment, enough judgment to challenge the output, and enough clarity about guardrails that they aren't constantly wondering what's allowed.

The measurement changes too. Leaders start asking better questions: Are we producing better work? Are people spending more time on work that requires human judgment, creativity, and relationships? Have we created repeatable ways of working that can survive the next tool or model change?

Building Block Teams Can Underestimate

Boiros has identified five building blocks of AI adaptation:

  1. Skills
  2. Workflows
  3. Guardrails
  4. Measurement
  5. Culture

The one most teams underestimate, she says, is culture.

“Culture shows up in what people actually feel safe and empowered to do every day," Boiros says.

AI asks people to learn in new ways and try things they might not be good at yet. They might also have to admit when they don't know something and rethink parts of a job they've spent years mastering. In cultures that reward certainty and polished answers, people default to caution. Some avoid AI entirely. Others experiment quietly and keep what they learn to themselves.

The teams making the most progress do the opposite. They create environments where curiosity is valued, experimentation is expected, and sharing what didn't work is as useful as sharing what did. When leaders use AI themselves, talk openly about what they're learning, and give people room to experiment responsibly, they send a powerful signal, and AI starts becoming a team capability rather than an individual productivity hack.

Why Resistance Isn't What Leaders Think 

After three years of training marketers and teams, Boiros says the most common source of resistance is fear, although it might not be obvious.

It often shows up as "I don't have time to learn another tool," or "I'm not sure this is relevant to my job," or "I tried AI once, and the result wasn't great." Underneath is uncertainty about role, career, and whether it's already too late to catch up.

"That's why I don't think the answer is simply more training," Boiros says. "What works better is creating space for people to learn without feeling like they're taking on a second job."

Her approach is to start with work people already need to do. Give them protected time to experiment. Make learning collaborative so peers can see how others are using AI and ask questions without feeling exposed. Small wins matter more than grand transformation plans. When someone uses AI to improve a real workflow or produce a better result, the conversation shifts from "Why do I have to use this?" to "Where else could this help me?"

What Boiros Will Explore at MAICON

This session is for leaders at all levels who need to drive AI adaptation, not just adoption, across a team. Boiros will unpack what has to shift after the pilot: building confidence and trust, turning scattered experimentation into repeatable workflows, reducing resistance without burning people out, and setting the processes and guardrails that make AI safer and easier to use.

What You'll Gain from Boiros' Session

Attendees will leave with a practical playbook they can use immediately, including:

  • The five building blocks of AI adaptation — skills, workflows, guardrails, measurement, and culture — and how to apply each
  • Real examples from three years of training marketers and teams
  • Specific ways to reduce resistance without burning people out
  • A framework for turning scattered experimentation into repeatable workflows that survive the next tool or model change

Join Us at MAICON 2026

Boiros joins an expert lineup focused on real-world AI strategy, implementation, and leadership.

Boiros will focus on what it really takes to adapt to AI: shifting not just tools, but how teams think, work, and make decisions. She brings a mix of curiosity, real-world experience, and just enough edge to spark honest conversation and meaningful takeaways.

Follow Boiros before MAICON 2026:

Join us at MAICON 2026 to hear Boiros and 50+ other AI and business leaders. Register today.

Cathy McPhillips

Cathy McPhillips is the Chief Marketing Officer at SmarterX and Marketing AI Institute

来源:Marketing AI Institute · marketingaiinstitute.com