The ENTERPRISE AI GUIDE in 1 page 📌

tgroenwals shared this post · 1h ago

The ENTERPRISE AI GUIDE in 1 page 📌

Leading AI in a business is a big job.

So I put my 9 most popular enterprise AI frameworks in one place:
📌 Get it free here: https://lnkd.in/gwtgqA3H

Start with what AI is:
👉 Types of AI: agents, generative, deep learning, classical ML and rules, and which one solves your problem

Then set strategy and value:
👉 The AI Strategy Wheel: 7 decisions every AI strategy has to make
👉 The AI Value Funnel: where value gets lost between interest and impact
👉 The Total Cost of AI Ownership: the costs your business case doesn't show

Drive adoption:
👉 4 Foundations For Successful AI Adoption
👉 Building AI Fluency: 16 ways to move from AI access to AI capability
👉 20 Ways To Measure AI Impact: practical KPIs for financial, operational, customer and workforce value

Keep it on track with governance:
👉 AI Governance For Every Leader: what the CEO, CFO, COO, CIO and CDO each need to know
👉 4 Layers of AI Guardrails: governance, operating model, process and system

These are the frameworks I use with executive teams across retail, energy, consumer goods & mining.

Download and share it with your team to guide your AI enablement.

♻️ Repost to help a leader get more with AI.
🔔 Follow Clare Kitching for insights on unlocking value with data & AI.

John Wernfeldt especially the guardrails one, most org stop at the policy layer and skip the operating model underneath

Gary Mitchell These frameworks are useful in building understanding. But beyond that, in building AI programmes that deliver value, we have to turn and look at the customer experience and the how the business works.

The superpower of AI is the empowerment of human interactions. I feel that many people see the objective as eliminating human interactions.

Really the business transformation landscape is quite simple. AI has a big part to play but we don’t start with AI. We start with the interactions we are seeking to empower.

1. Productivity of Individuals (e.g. copilot, ChatGPT)
2. Collaborative work (e.g. TEAMS)
3. Decision support (dashboards, data)
4. Workflow / capability improvement
5. Op Model / Customer Experience Transformation

Each of these have distinctly different business cases, different AI options, programme challenges, and governance needs.

If looked at together as “implementation of AI” it is confusing, but if broken out as above, decision making and governance become much easier to understand. Especially for the non-AI executives who must make decisions and do the governance.

We must remember that understanding of AI is not the objective. The objective is transformation. Using AI as a powerful tool to support this.