Nicole M. Radziwill, PhD, MBA
Frameworks for Smarter AI

Quality is the AI strategy that actually works.

It's easy to tell leaders what they should do, or what they should think about. It's much harder to guide them as they discover how to apply those best practices in the unique ways that are best for their organizations.

Bridging the gap between academic rigor and operational excellence, these pioneering frameworks provide the structural integrity you need to reinvent work with AI.

Nicole M. Radziwill
Find Nicole on LinkedIn
Framework No. 1

Quality-First AI.

Sometimes, you just need to get to market the fastest - the bugs are OK, you can fix them later. You just can't miss the opportunity. But when you care about sustainable value from AI, a quality-first approach is essential... or the AI you embed in your workflows could cause far more harm than good.

The Foundation is your quality system, which provides AI assistants the context for what your organization does and why. It's the context that isn't captured by surveilling your clicks, monitoring your Slack channels, or synthesizing your knowledge repository. Activation is where the work happens, linking each person's individual identity to the results your organization needs them to achieve together. Self-Renewal is the result that keeps your culture driving value from AI, never neglecting the pivotal role of humans in the value creation process.

Read the Paper or Use this model at your company.

Gen AI Value Creation Pyramid
Framework No. 2

What’s Your AI Persona?

If you're not an early adopter of AI, your company may consider laying you off. But this is totally the wrong move. Only 15.7% of people are EXPERIMENTERS, but value creation with AI requires a more nuanced social fabric. And the good news is: leaders can strategically engineer this using AI Personas (part of the Team-X Collaborative Intelligence System.)

By working with thousands of people on hundreds of teams, our research uncovered 7 cognitive archetypes that shape how we engage with AI. By mapping team members to specific personas, leaders can align cognitive strengths, accelerate adoption, and drive meaningful innovation.

Learn More Take the Assessment
EXPERIMENTER
SHAPESHIFTER
OPTIMIZER
INTEGRATOR
STABILIZER
OBSERVER
STEWARD
Framework No. 3

Gen AI Value Creation Pyramid.

Most organizations start at the bottom with process automation. Nicole and her collaborators studied early adopters to uncover this pyramid, which illustrates how emergent leaders have climbed toward mixed-strategy thinking, integrating AI across functions rather than getting stuck just saving time at the individual and task level.

Level 4 Visionary Innovations
Level 3 Transformation & Growth
Level 2 Collective Intelligence
Level 1 Individual Improvements
Gen AI Value Creation Pyramid
Read about it in Harvard Business Review (2024)
Framework No. 4

The CIA Model.

A decision model for efficient and effective AI implementation grounded in three pillars: Connectedness of people and systems, Intelligence embedded into processes and workflows, and Automation - which never has to be all-or-nothing. Choose the right combination of CIA levels for the business problem you're solving from 1000 options to make sure you're not swatting a fly with explosives.

Designed for all organizations, including those operating in regulated, high-stakes, or complex environments where AI can't simply be deployed and left unchecked.

C
Connectedness
I
Intelligence
A
Automation
Connected, Intelligent, Automated (2020)
Find CIA on Amazon
Framework No. 5

AIADV Framework for AI Data Quality Assurance.

Thinking about AI as either a lever IN or the end result OF a data supply chain can help you find quality issues that improve the performance of your AI-enabled workflows and AI agents. AIADV is a data value mapping technique that makes this problem-solving easier. Read More in this blog post. Clients have used this for:

AI Workflow Integration90%
Data Readiness85%
Value Realization60%
Organizational Alignment50%

AIADV (Radziwill, 2020)

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