According to McKinsey’s 2025 State of AI report, 88% of companies now use AI in at least one business function. But out of nearly 2,000 companies surveyed, only about 5.5% reported that AI is generating meaningful financial returns.
The gap between AI adoption and results is not a technology problem. It is a strategy and leadership problem; one that Hélène knows how to solve.
Hélène Bergeot is a Fractional CMO at CAC Media & Publishing, specializing in international expansion, global brand strategy, and licensing. She has spent 30-plus years leading marketing across over 15 international markets, and she recently completed the Artificial Intelligence: Implications for Business Strategy program from the MIT Sloan School of Management and MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).
Lucky for us, Hélène is sharing her takeaways here.
“The MIT course AI Implications For Business I just completed gave me a thorough understanding of the nuances of the potential business solutions offered by AI, their practical applications and also about the ethical concerns to consider:
- Does a company have enough data to actually leverage machine learning?
- How to ensure that the available data does not create a biased model?
- How does an AI project align with the company strategy in terms of expected results?
- How will the results of the AI initiatives be assessed and how can the initial prototype be scaled?
- What will be the impact of an AI implementation on the workforce?
Many aspects need to be considered before embarking on an AI journey; my biggest take-aways are about assessing the best way human and machine can collaborate and about establishing a comprehensive roadmap to implement any AI initiative. Last but not least, this is more than implementing a new technology; this is about change management.
AI will continue to evolve and offer innovative solutions for companies to develop a strategic advantage; the key is all about identifying the best way to deploy AI initiatives, tailored to the DNA and priorities of a specific company.
This is where the ‘how’ takes more importance than the ‘what’.”
AI Adoption Framework Built for Business Strategy
If you are a CEO trying to answer these questions for your own marketing department, CAC Media has developed the SCALE framework specifically for this challenge.
SCALE, which stands for Systems Audit, Content Guardrails, Automation with Checkpoints, LLM Discoverability, and Evidence-Based Measurement, is a practical, sequential framework developed by founder Corinne Cavanaugh for embedding AI into your sales and marketing operations with the discipline required to protect your brand and produce measurable revenue outcomes.
Download the SCALE Framework to get the full playbook, including how to audit your current systems, build content guardrails, and measure what matters.
What This Means for Your Company Right Now
The MIT course makes one thing clear: tool adoption velocity isn’t nearly as important as asking the right questions before deploying. The importance of aligning AI initiatives to specific business outcomes cannot be understated, and the internal capability to measure and sustain the workflow needs to be planned.
That kind of strategic clarity is not something a software subscription to your favorite LLM provides. It comes from leadership, pattern recognition, and the experience of having navigated enough technology cycles to know how to modernize sustainably.
At CAC Media, we bring that experience into every engagement. Whether you are just beginning to think about AI-first marketing or already have tools you are using, the best conversations starts with your specific situation, not generic guidance.
Book a free 20-minute strategy session to talk through where your company is and what disciplined AI adoption looks like for your marketing department.
About Hélène Bergeot
Hélène Bergeot is a Fractional CMO at CAC Media & Publishing, specializing in international expansion, global brand strategy, and licensing. She has spent 30-plus years leading marketing across international markets. At Jazwares, a Berkshire Hathaway company, she provided strategic direction for 15-plus brands including Squishmallows, Pokémon, Hello Kitty, and Fortnite. At Wizards of the Coast, she built the Wizards Play Network to 5,000-plus retail partners globally and negotiated a Twitch partnership for Magic: The Gathering. At Mythical Games, she turned complex franchise IP into fan experiences that resonated across international markets. She recently completed the Artificial Intelligence: Implications for Business Strategy certificate program at MIT Sloan Executive Education.
More from Hélène Bergeot
FAQ
Sloan Artificial Intelligence: Implications for Business Strategy program is a six-week online course covering machine learning, generative AI, robotics, and the future of AI. It is designed for executives and senior leaders, not engineers. The focus is on the organizational and managerial implications of AI: how to assess readiness, align AI initiatives to business strategy, measure results, and scale what works.
According to McKinsey’s 2025 State of AI report, 88% of companies use AI in at least one function, but only about 5.5% report meaningful financial returns. The gap is not a technology problem. It is a strategy and leadership problem. Most companies adopt tools before defining what success looks like or building the organizational infrastructure to sustain it. The companies seeing real returns are those that treat AI adoption as a change management initiative, not a software rollout.
SCALE is a strategic framework developed by CAC Media & Publishing for embedding AI into a marketing department with discipline rather than chaos. It stands for Systems Audit, Content Guardrails, Automation with Checkpoints, LLM Discoverability, and Evidence-Based Measurement. It gives marketing leaders a sequential, practical roadmap for adopting AI in ways that protect brand integrity and produce measurable revenue outcomes.
The MIT Sloan AI program identifies six critical questions every executive should answer before committing to AI adoption: Does your company have enough clean data to leverage machine learning? How will you prevent data bias from affecting model outputs? How does the AI initiative align with your company strategy? How will results be assessed? How will a successful prototype be scaled? And what will the impact be on your workforce? These questions determine whether AI investments compound into competitive advantage or become expensive experiments.
AI adoption is the act of implementing tools and systems. AI strategy is the discipline of knowing which problems to solve, in which order, with which safeguards, and how to measure whether the investment is working. Most companies have AI adoption. Very few have AI strategy. The difference is visible in the results: McKinsey found that companies with a clear AI strategy aligned to business objectives are significantly more likely to achieve measurable ROI than those pursuing isolated experiments.
A fractional CMO brings the pattern recognition of having navigated multiple technology modernization in several industries. They assess where your marketing operation has the highest-value opportunities for AI-powered modernization, build the governance and guardrails before scaling, define the metrics that connect AI activity to revenue outcomes, and mentor your team through the transition. They arrive with a charter to increase revenue, not a mandate to implement a preferred tool stack.
Our true north
You don’t have to figure this out alone.
Our fractional CMOs embed on your leadership team, build the revenue systems you need, mentor your technicians, and deliver the growth you’ve been working toward. You get time back. Your marketing works.
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