Organizational Assessments

This post was originally featured in the August 27th, 2025 newsletter found here: INBOX INSIGHTS, August 27, 2025: Organizational Assessments, 2025 Hiring Demand by Industry

The Organizational Readiness Assessment That Actually Works

I want to tell you a story about one of my more spectacular failures. Years ago, I was tasked with rolling out a new project management system—MS Project 2010 and SharePoint. On paper, it was a solid platform. In reality, it was a disaster. I tried to launch it not once, not twice, but three separate times. Each time, it failed.

Why? Because I was never given a clear “why.” I couldn’t tell the teams why we were switching, other than “leadership wants this.” The teams, who were perfectly happy with their own tracking tools, were never consulted. The new platform didn’t solve their problems; it just created new ones. The result was a massive waste of time, money, and, quite frankly, my sanity.

Sound familiar? Today, the pressure isn’t about SharePoint; it’s about AI. Every leader, every team, every company is feeling the heat to “do something with AI.” So we jump. We sign up for a tool, we task a team with “finding a use case,” and we cross our fingers. More often than not, it ends the same way my SharePoint project did: with a fizzle, not a bang.

The problem wasn’t the technology itself—it was that nobody had honestly assessed whether we were actually ready for this kind of transformation.

That’s why I’ve developed what I call the “brutally honest” readiness assessment – based on the 5P Framework. It’s not just a quick checklist you can breeze through to feel good about yourself. This thing forces you to confront the real gaps in your organization, and trust me, there are always gaps.

Why Most Readiness Assessments Miss the Mark

The thing about most AI readiness assessments is that they’re designed to make you feel confident about moving forward, not to actually prepare you for success. They ask surface-level questions like “Do you have leadership buy-in?” without digging into what that actually means.

Real readiness assessment means asking the uncomfortable questions. Like: Does your team actually know how to use AI beyond “write me a blog post”? (Spoiler alert: probably not.) Have you identified every single person who will be impacted by this change? Do you know what happens when your lead scoring suddenly triples your qualified leads?

The Five Pillars, But Deeper

The assessment I’ve built covers the same five foundational areas as the 5P Framework—Purpose, People, Process, Platform, and Performance—but it goes far beyond just checking boxes. Each section includes dozens of specific questions designed to uncover the real state of your readiness.

Purpose: Beyond “We Want to Use AI”

Most organizations think having a purpose means saying “we want to improve efficiency with AI.” That’s not a purpose, that’s a wish. The purpose section of this assessment digs into whether you’ve actually connected your AI initiatives to specific business objectives, whether you’ve documented success metrics, and whether leadership has articulated how this connects to your long-term vision.

One question that always trips people up: “Is there consensus among stakeholders regarding initiative scope, boundaries, and expected outcomes?” I can’t tell you how many times I’ve seen projects derail because sales thought they were getting one thing, marketing expected another, and IT was building something completely different.

People: The Make-or-Break Factor

People are the linchpin of any successful AI implementation, and the assessment reflects that reality. We’re not just talking about whether someone on your team has used ChatGPT. It’s a good starting point, but your team needs more experience than that.

This section breaks down into three critical areas:

Team AI Literacy and Skills: Do your people actually know how to do deep research with AI? Can they create effective prompts? Do they understand the limitations? If generative AI has only been used at the surface level (like to create content), you’re not ready to effectively leverage AI for complex business processes.

Leadership and Stakeholder Buy-In: Is there visible, active executive sponsorship? Have you identified all the stakeholders who need to be engaged? I’m talking about everyone—if you’re implementing automated lead scoring, that impacts sales, marketing, customer support, development, IT, and leadership. Have they all been looped in?

Change Management: Here’s where it gets real. Real tough, that is. Is your organizational culture actually receptive to workflow changes? Do you have established change management methodologies? Have you identified potential resistance and addressed it proactively?

One of my favorite questions in this section is: “Have early adopters and internal champions been identified to support adoption and engagement?” Change management is often seen as a cultural shift, and you need your culture carriers on board to support your initiatives.

Process: The Foundation Everything Else Builds On

The process section exposes something most organizations don’t want to admit: their current processes aren’t well-defined or documented. If you can’t clearly articulate how something works today, you definitely can’t improve it with AI tomorrow.

Existing Workflow Efficiency: Are your current processes actually documented and understood by all stakeholders? (Even at Trust Insights, we don’t have everything documented perfectly—it’s an ongoing challenge.) But here’s the thing: the more you have documented, the easier it becomes to introduce new technology and manage change.

AI Governance and Ethical Guidelines: Do you have established governance structures for AI implementation? Are there documented ethical guidelines? Have you identified potential risks and mitigation strategies for each initiative?

This is where the assessment gets into the nitty-gritty of compliance requirements, regulatory considerations, and industry-specific guidelines. If you’re handling PHI, PII, or operating under GDPR, HIPAA, or COPPA regulations, you need to know how AI fits into those requirements.

Platform: More Than Just “Does It Work?”

The platform assessment goes way deeper than basic compatibility questions. We’re talking about whether your current martech stack can actually integrate with AI solutions, whether you have the APIs and data exchange mechanisms necessary, and whether your existing technology environment is flexible enough to accommodate new solutions.

Technical Expertise and Support: Do you have sufficient technical knowledge to implement and manage AI solutions? Are IT and technical resources allocated and committed? Do you have access to specialized expertise, either internal or external?

Infrastructure Readiness: Can your current technology environment actually support AI solutions? Have computing, storage, and processing capabilities been assessed? Is your security environment sufficient for sensitive data use?

Performance: The 6Cs Deep Dive

This is where the assessment gets seriously comprehensive. The performance section breaks down into six critical areas—what I call the 6Cs of data quality: Clean, Complete, Comprehensive, Chosen, Credible, and Calculable.

Each C includes multiple detailed questions about your data foundation, from whether your data is free from significant errors and duplications to whether you have established processes for ongoing data quality maintenance.

For example, under “Credible,” we ask: Are your data sources reliable and trusted? Have you documented data sources and origin for key assets? Do you have established standards for data source evaluation? Have potential data biases been identified and addressed?

The Real Assessment

When you complete this assessment honestly (and I mean brutally honest), most organizations score around 2.3 out of 5. That’s not a failure—that’s reality. It means you have work to do before you start implementing AI solutions.

Scores below 3 in any category indicate areas requiring focused attention before proceeding with implementation. Categories scoring 3-4 represent areas for ongoing improvement. Only categories scoring 5 indicate organizational strengths that can actually support successful AI adoption.

Why This Level of Detail Matters

I know this feels like a lot. Trust me, I get it. But here’s what I’ve learned from watching countless AI implementations: the organizations that succeed are the ones that do this deep assessment work upfront. The ones that skip it? They’re the ones calling me six weeks later asking how to fix the chaos.

This assessment forces you to move from vague feelings about readiness to concrete evaluation of your organizational capabilities. It identifies gaps before they become expensive problems. And it creates a roadmap for addressing those gaps systematically.

Your Next Step

When it comes to initiatives, where are the failure points? Is it people? Is it the process? How long do new things last, and how quickly do those ideas get shelved? The next time you want to introduce a new technology, or change a process, take a step back and assess the readiness of your organization with a critical eye.

Are you being honest about the “readiness” of your organization? Reply to this email or join our free Slack group, Analytics for Marketers.

– Katie Robbert, CEO

p.s. If you want a copy of the 5P Readiness Assessment, it is available in our new course, the AI-Ready Strategist, live on September 2nd. You can pre-order now through August 29th with the discount code: strategy2025 – go to trustinsights.ai/aistrategycourse

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