The 10/20/70 Rule

The 10/20/70 Rule : Why Your Workforce is Your Biggest AI Bottleneck

Last month, I was catching up with a friend who runs marketing for a mid-sized software company. She was frustrated—and I mean really frustrated. Her company had just spent six figures on an AI-powered marketing automation platform. The demos were impressive. The sales team promised it would revolutionize their campaigns. Leadership was thrilled.

Three months later? Maybe four people on her 25-person team actually use it. The rest have quietly gone back to their old spreadsheets and manual processes. Some have started using ChatGPT on their personal phones to do the work instead—completely outside IT’s visibility.

Sound familiar? If you’re nodding along, you’re not alone.

The Real Reason Your AI Investment Isn’t Paying Off

Here’s what nobody wants to admit: the problem isn’t the technology. It’s us. It’s the humans.

Boston Consulting Group studied AI implementation across organizations and found something that should make every executive pause before signing another software contract. They call it the 10/20/70 rule: successful AI adoption depends roughly 10% on algorithms, 20% on technology and data, and 70% on people and processes.

Let that sink in. Seventy percent of your AI success hinges on whether your workforce can actually use what you’ve bought.

We’ve gotten this completely backwards. Most organizations spend 80% of their AI budget on platforms and tools, then wonder why adoption stalls. It’s like buying a professional-grade stand mixer and expecting to suddenly produce bakery-quality croissants. The equipment matters, sure—but it’s maybe 20% of the equation. The other 80% is knowing what you’re doing with it.

What “AI-Readiness” Actually Means (And What Happens Without It)

When I talk about “AI-Readiness,” I’m not talking about everyone becoming a data scientist. AI-Readiness simply means your team understands when to use AI tools, how to use them effectively, and why the outputs matter for their specific work.

Without this readiness, three predictable things happen:

Rejection: People avoid the new tools entirely. They’re too busy, too confused, or too skeptical. The platform sits there, expensive and unused, while everyone keeps doing things the old way.

Workarounds: Some employees create elaborate systems to look like they’re using the AI while actually bypassing it. I’ve seen teams manually enter data into AI platforms, then ignore the outputs and do their analysis in Excel anyway. All the effort, none of the benefit.

Shadow AI: This is the one that should keep you up at night. When official tools are too complicated or restrictive, people find their own solutions. They paste confidential customer data into free AI chatbots. They use personal accounts for work projects. They share proprietary information with tools that have no enterprise security agreements. Your data is walking out the door, and you don’t even know it.

A Practical Audit: Applying the 5P Framework

Before you buy another platform—or abandon the ones you have—take a hard look at your current state. I use the 5P Framework for this: Purpose, People, Process, Platform, and Performance. Here’s how to audit your AI readiness:

Purpose: Why did you implement this AI tool in the first place? Can you articulate the specific business problem it solves? If leadership can’t clearly explain the “why,” your team definitely can’t either. And if they don’t understand why they should use it, they won’t.

People: This is your 70%. Who actually needs to use this tool daily? What’s their current comfort level with AI? Have they received training beyond a single onboarding session six months ago? Do they have time built into their workload to learn and experiment, or are they expected to figure it out while hitting the same deadlines?

Process: Where does the AI tool fit into existing workflows? Is it replacing a step, augmenting one, or adding entirely new work? If you’ve layered AI on top of existing processes without removing anything, you’ve just made everyone’s job harder.

Platform: Now—and only now—look at the technology itself. Does it actually do what you need? Is it integrated with systems people already use? Can your IT team support it? Is it accessible to people with different abilities and technical backgrounds?

Performance: How do you know if it’s working? What metrics are you tracking? Are you measuring adoption, outcomes, or both? If you can’t answer this, you’re flying blind.

Your Monday Morning Checklist

You might not have the authority to overhaul your company’s entire AI strategy. But you can start somewhere. Here’s what you can do this week:

☐ Ask five people on your team: “What AI tools are you supposed to be using, and what are you actually using?” Listen without judgment. The gap between those answers tells you everything.

☐ Check your shadow AI exposure: Survey your team (anonymously if needed) about what external AI tools they’re using for work.

☐ Audit one tool, deeply: Pick your most expensive or most strategic AI platform. Answer the 5P questions above. Be honest.

☐ Calculate your real adoption rate: Not logins—actual usage. How many people used the tool to complete real work in the last 30 days?

☐ Identify your bright spots: Find the two or three people who are successfully using your AI tools. What’s different about them?

Next week I’ll ask (and answer) the question: Who Owns AI When Everyone Owns AI?

How are you investing in your people? Reply to this email or join the conversation in our Free Slack community, Analytics for Marketers!

– Katie Robbert, CEO

Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.