AI Strategy Frameworks. Part 2.

 

How can teams bridge strategic ambitions with the practical steps to deploy, scale, and govern AI effectively? Our AI Strategy Frameworks (Part 2) presentation provides the toolkit to turn opportunity into organized execution. It brings together strategy models that define direction, value creation approaches that pinpoint impact, execution blueprints that drive delivery, scaling frameworks that sustain adoption, and governance systems that ensure accountability. Each framework sharpens decision quality, accelerates alignment across business and technical teams, and reduces wasted experimentation.

Grounded in current industry practices, these frameworks help teams achieve faster innovation cycles, stronger collaboration, and higher returns from AI investments. Strategic consistency replaces fragmented experimentation, while governance discipline mitigates risk and builds trust. As these effects compound over time, early AI projects progress into scalable engines of performance, resilience, and long-term competitive differentiation.

Strategy

To realize true value and achieve sustained advantage with new technology, AI shouldn’t be positioned just as a capability, but as a long-term source of competitive advantage.

The Pioneer–Migrator–Settler Map frames AI strategy as a dynamic trajectory rather than a static state. It articulates whether the current portfolio emphasizes value imitation, value improvement, or value innovation, and whether that posture is intentional or accidental. As progress movements visualize over time, the map drives more honest conversations about aspiration versus reality. It also provides a shared language to discuss competitive positioning, making it easier to align investment decisions with where the organization actually wants to lead rather than where it happens to operate today.

While ambition sets direction, execution constraints often determine outcomes. The BCG’s 10–20–70 Model reframes AI challenges away from a narrow focus on algorithms and platforms. This lens is especially useful when AI initiatives stall despite strong technical foundations. By diagnosing friction in skills, incentives, governance, and prioritization, the model helps teams redirect effort toward the real bottlenecks that limit scale and impact.

Strategic intent must also pass a reality check. The AI Feasibility Assessment evaluates where value originates, who depends on the system, and what capabilities are required to deliver results. It balances numerical ROI with non-financial gains such as decision quality and operational speed, so that feasibility discussions reflect the full value equation rather than short-term cost logic alone.

Value Creation

Value creation shifts the conversation from strategic intent to economic substance. Its purpose is to make AI value explicit, comparable, and defensible, especially in environments where enthusiasm can outpace financial discipline.

Value Engineering decomposes AI value into tangible and intangible drivers and clarifies where returns actually come from and how they accumulate over time. By separating revenue growth, cost efficiency, and productivity gains from softer outcomes such as trust, ethics, and risk reduction, it avoids the common trap of overstating ROI through narrow metrics. As more AI initiatives compete for capital, this approach allows leaders to compare use cases on a consistent economic logic rather than narrative appeal.

Cost discipline becomes more nuanced when scale enters the picture. Initial implementation costs, whether driven by custom development or off-the-shelf solutions, rarely tell the full story. The Total Cost of Ownership (TCO) view and the Cost vs. Value Realization curve break down how AI economics evolve across time horizons. These tools highlight how integration complexity, usage growth, infrastructure demands, and organizational change introduce second-order costs that surface well after launch. At the same time, they show that value often compounds nonlinearly once systems stabilize and adoption deepens.

Execution

Many AI strategies falter at the point of transition from approved ideas to durable systems that operate in real environments. CPMAI’s AI Project Go/No-Go Decision Model introduces a disciplined gate before resources fully commit. By testing business, data, and implementation feasibility in parallel, the model prevents technically impressive but operationally fragile initiatives from advancing.

For product-centric organizations, execution clarity also depends on choosing the right AI interaction pattern. The AI Product Experience Archetype distinguishes between chat, tool, copilot, and agent-based experiences. Rather than defaulting to autonomous agents because they appear more advanced, teams can align product design with user trust, task structure, and risk tolerance.

Delivery speed and consistency hinge on how development work flows across teams. Development Lifecycle Optimization highlights how AI-enabled delivery compresses traditional stages without sacrificing validation. By collapsing discovery, experimentation, and build cycles, it reduces frictions created by siloed ownership and fragmented data.

Finally, execution maturity depends on knowing where machines add leverage and where human judgment remains essential. The Human-Machine Task Distribution Map visualizes that boundary across task complexity and decision criticality. This framework prevents role confusion, builds trust in AI outputs, and supports responsible scaling.

Scaling

As AI initiatives mature, scaling becomes more about managed progression where technical ambition and organizational trust advance in parallel.

The Data-to-Strategy Impact framework clarifies how analytics capabilities evolve as AI systems absorb more data and influence higher-stakes decisions. It shows that moving from operational intelligence to predictive and prescriptive analytics is not merely a tooling upgrade, but a shift in how organizations compete. Each step along the curve demands greater rigor in data foundations, governance, and deployment maturity, while also delivering disproportionate gains in business impact.

Once systems operate at scale, performance scrutiny intensifies. The Model Performance and Confusion Matrix, paired with Interpretability-Performance Trade-off, brings that scrutiny into focus. Performance metrics across training, validation, and real-world testing reveal how models behave under varied conditions, exposing stability, drift, and edge-case risk. In parallel, the interpretability curve forces explicit trade-offs between accuracy and explainability, a tension that grows sharper as models influence customer outcomes, pricing, or compliance-sensitive decisions.

Governance

AI risk is no longer hypothetical, and governance can no longer be informal. The Gen AI Risk Assessment decision tree establishes a clear way to reason about exposure before systems are deployed. Risks are categorized into input risk, system risk, and output risk, which prevents teams from collapsing all AI risk into a single judgment. This structure helps organizations distinguish between acceptable experimentation and activities that require stronger safeguards or should be avoided altogether.

Once risks are identified, the Risk Treatment Cost-Benefit model frames risk reduction as an investment choice. By comparing expected loss, probability of occurrence, and mitigation cost, leaders can justify security and compliance spending in business terms. 

Ethical considerations require a different kind of rigor. The Triadic AI Ethics Assessment operationalizes ethics across system design, data stewardship, and deployment lifecycle. By mapping ethical principles such as fairness, accountability, explainability, and privacy across information, cognitive, and physical domains, it avoids the treatment of ethics as a one-time checklist. Instead, it reinforces that ethical performance evolves as systems scale, interact with users, and influence real-world outcomes.

Conclusion

What ultimately differentiates successful AI programs is not model sophistication, but coherence across decisions. [Name] provides the connective tissue that links ambition to economics, execution to scale, and innovation to responsibility. Apply these frameworks to move beyond isolated wins toward AI systems that compound value, earn trust, and remain durable as technologies, markets, and expectations evolve.

https://tinyurl.com/3m9msphv

The anti-pitch outreach framework

 

The reason why prospects ignore you.
You sound like everyone else.

After analysing 10,000+ outreach messages, I have discovered why 98% feel like spam.

Because they basically are.
Even the ones labelled "personalised."

Most teams call this personalised outreach:

Hi [First Name], I noticed you work at [Company]…

Then a bunch of copy-pasted pain points ripped from some blog.
Same template blasted to 500 people.
Zero context beyond a LinkedIn headline.

And then they wonder why their reply rate is stuck at 2%.

This is the pattern I see quite often:

1,000 messages sent. Single-digit replies. One sad meeting booked.

Personalisation? Dropping company names into a mail merge.

This is not real personalisation.

Real personalisation requires three layers of context.


Here is what the three layers look like:

Layer 1️⃣: Company intelligence

Funding rounds, acquisitions, leadership changes.
Tech stack and tools in play.
Signals of growth stage and competitive moves.

Layer 2️⃣: Individual insights

What their role actually cares about.
Recent posts, comments, engagement.
Career trajectory and level of influence.

Layer 3️⃣: Timing relevance

Budget cycles and planning windows.
Team growth or restructuring.
Industry events, regulatory shifts, seasonal business patterns.

Here is what changes when you get this right.

When you stack these three layers, outreach stops looking like spam and starts feeling like relevance.

That is when replies jump into double digits.
That is when prospects literally say:
"Finally, someone who gets our business."

You cannot fake relationships.
But you can build the context that makes them possible.

Stop spamming more. Start personalising better.

Outbound teams winning today are not sending more messages. They are sending smarter ones. Outreach that feels human, builds trust, and actually gets the meeting.

https://tinyurl.com/ytd3fvkf

The TEA Framework: Time, Energy, Attention

 

The TEA Framework diagnoses which productivity pillar is broken: Time, Energy, or Attention. Most people apply random solutions without knowing their actual bottleneck.

Time equals calendar capacity, hours on right priorities, saying no, delegation. If no time for what matters, energy and attention are irrelevant. Example: calendar wall-to-wall meetings, no space for deep work, time is bottleneck.

Energy equals sleep quality, physical health, mental state, circadian alignment. If time but no energy, you stare at screen accomplishing nothing. Example: blocked three hours for strategy but exhausted on five hours sleep, energy is bottleneck.

Attention equals eliminating interruptions, single-tasking, goal clarity, mindset management. If time and energy but can't focus, waste best hours on shallow work. Example: two hours free, well-rested, can't focus past five minutes, attention is bottleneck.

Quick diagnostic: Can you sit for twenty-five uninterrupted minutes on important task right now? No equals attention problem. Yes but no twenty-five minutes free equals time problem. Yes and have time but too exhausted equals energy problem.

Fix hierarchy: Time first, energy second, attention last. Don't fix attention when time is broken, wasted effort. Implementation: diagnose bottleneck, pick one fix from that pillar, measure for one week, iterate based on data.

Common mistakes: fixing all three at once creates overwhelm, fixing attention when time broken wastes effort, skipping measurement means no idea if interventions work, giving up after one week when most fixes need two to four weeks.

Follow me Dan Murray for more on habits and leadership

The 4 types of ‘Why’: What is the driving force behind your product?

 

Catherine (Kit) Ulrich

I recently wrote about a framework I created called the Ladder of Needs, a simple tool for product people to create a compelling vision. It combines the best of Simon Sinek’s ideas from Start with Why and Clay Christensen’s classic framework of ‘jobs to be done’.

So, how do you determine the ‘Why’ behind your product?

Start by considering this gem from Jeff Bezos:

“People often ask what will be different in the world in 10 years, the more important question is what will be the same” — Jeff Bezos

So true, because the fundamentals of what people want and need are exactly that…fundamental truths. In my time as a product leader, I have found 4 models that apply to almost all consumer experiences and products. These are not mutually exclusive — they are ideas that overlap in many ways, but one will likely call to you more than the others.

What is your customer’s scarcest resource? It tends to be either money, time, energy.

You may have seen this meme on Twitter or Instagram before (I’d love to know whom to credit with it’s creation). It’s a great framework for products.

This is why Bezos’ answer to his own question, ‘what will be the same in the world in 10 years’, was that Amazon customers would always want lower prices (money) and faster shipping (time). Amazon’s strategy was built by focusing on these core customer needs.

This is also why Uber isn’t in the business of selling rides, it is in the business of selling time.

I have found that Tony Robbins is a bit of a lightning rod figure. When I mention his name people generally respond in one of two camps: ‘I love him, he is awesome’ or ‘he is a cult leader’. No matter what your personal perspective is, his framework on the 6 core human needs is still a classic.

Tony advocates that there are 6 core human needs that drive our behaviors:

• Certainty: The need for safety, stability, predictability, comfort
• Uncertainty/Variety: The need for surprise, excitement, novelty, change
• Love & Connection: The need for social attachment, approval. To feel connected and loved
• Significance: The need to have meaning, pride. To feel special and wanted
• Growth: The need for constant development, intellectually, emotionally, spiritually
• Contribution: The need to give to others. To protect, care for, serve

Even more fascinating, is that Tony believes any experience, product, or action is addictive if it serves 3 of these needs.

For example, Facebook solves for (1) love & connection…by feeling connected with your friends, (2) significance…by receiving feedback/prominence from what you post and (3) variety….you never know what will appear in your feed.

Taking a slightly more negative spin, many products also solve for one of the seven deadly sins:

• Pride
• Greed
• Lust
• Envy
• Gluttony
• Sloth
• Wrath

Targeting one of these seven deadly sins often makes a product addictive. In this framework, Facebook solves for pride. Uber and Amazon solve for sloth and greed.

Last but not least, several psychologists have offered up frameworks for the purpose of life:

• For Freud, it was the search for pleasure
• For Nietzsche, it was the search for power
• For Frankl, it was the search for meaning

One key principle behind behavior change and our cognitive biases is that we seek pleasure and avoid pain. This has always been a great insight to use as you design your product experiences.

We are seeing the rise of products and services that focus on customers’ search for meaning. For example, the rise of mindfulness and meditation products. Or, products such as Toms and Feed which give back to the world.

https://tinyurl.com/3j5b8cnd

RoundMap® : VEVA Model

 

Essential Collaboration Principles (VEVA) for Building Future-Fit Organizations

The VEVA model, integral to the RoundMap framework, encapsulates the collaborative essentials for building future-fit organizations. In an era of changing times, business conduct is shifting fundamentally. We are moving from a paradigm of egocentricity, driven by fierce competition and shareholder value, to one of ecocentricity, fueled by cooperation and stakeholder value.

This transformative shift implies moving away from the limiting proportions symbolized by Da Vinci’s Vitruvian Man to the boundless potential of the human mind, represented by the Vitruvian Woman. She embodies a more inclusive and expansive view of human capability, aligning with the core values of VEVA: Versatility, Equitability, Vitality, and Agility.

By embracing VEVA’s core principles, we highlight the importance of feminine traits in business, such as nurturing and inclusivity, to foster a balanced and holistic approach to organizational development.

Let’s delve deeper into these essential components and their roles within the RoundMap framework :

Versatility

Versatility emphasizes the organization’s ability to adapt to diverse roles, challenges, and changing environments. This principle fosters flexibility and resilience, enabling the organization to pivot effectively and seize emerging opportunities. Organizations can develop multi-skilled teams and dynamic processes that enhance innovation and problem-solving capabilities by prioritizing versatility. Ultimately, versatility empowers the organization to remain agile and competitive in an ever-evolving market landscape. (https://tinyurl.com/yechbd3u) 

Equitability

Equitability ensures that value is distributed fairly and inclusively, fostering a culture of trust and mutual respect. This principle is essential for creating a supportive environment where all stakeholders feel valued and engaged, promoting collaboration and innovation. By prioritizing equitability, organizations can bridge gaps, reduce disparities, and harness diverse perspectives to drive sustainable success. Ultimately, equitability strengthens the organizational fabric, enabling it to adapt and thrive in an ever-evolving business landscape. (https://tinyurl.com/yechbd3u) 

Vitality

Vitality focuses on the overall health and robustness of the organization, ensuring it remains strong and resilient. This principle is critical for sustaining long-term growth and the capacity to navigate challenges effectively. By prioritizing vitality, organizations can maintain financial stability, operational efficiency, and a thriving workforce. Vitality enables the organization to consistently perform at its best, fostering a sustainable and prosperous future. (https://tinyurl.com/yechbd3u)

Agility

Agility highlights the organization’s capacity to adapt swiftly to changing conditions and market dynamics. This principle is essential for competitiveness and responsiveness in a fast-paced business environment. Organizations can quickly pivot strategies, embrace innovation, and capitalize on emerging opportunities by prioritizing agility. Ultimately, agility ensures that the organization remains dynamic and resilient, capable of thriving amid uncertainty and continuous change. (https://tinyurl.com/yechbd3u)

Conclusion

By adopting the VEVA principles, we associate the way forward with essential feminine traits in business, such as nurturing and inclusion. This underscores the profound significance of integrating these crucial components to build a robust, adaptable, and inclusive organization ready to thrive in the future.

Embracing Versatility, Equitability, Vitality, and Agility as foundational pillars, VEVA fosters a balanced and holistic approach, driving sustainable success and innovation. Let’s harness the power of these qualities to create a future-fit organization where every stakeholder flourishes.

Together, these elements form the wheels that drive our vehicle toward a future where businesses are not just fit to compete but are built to last and thrive sustainably. The journey towards this future is navigated through collaboration, inclusivity, and a commitment to shared success, making the RoundMap framework a blueprint for enduring prosperity.

https://tinyurl.com/4zy4ds2k

Locus Focus Vs ‘Hocus Pocus’

 

Measuring success is part of the governance and management responsibility of all non-profit organisations. This responsibility augments obligations related to compliance with legal, regulatory and ethical requirements

‘Hocus Pocus’

According to vocabulary.com, ‘hocus-pocus‘ is an illusion or a meaningless distraction that tricks you in some way. Originally derived from invocations used in magic shows (like ‘abracadabra’), it’s actually fake Latin.

Some of what passes for performance and conformance governance might also be called hocus pocus, as it does not necessarily use the most appropriate indicator or measure to permit a valid evaluation to be carried out.

Confusion can also arise from leaders using certain terms interchangeably. Differentiating between measurement terms and establishing shared understandings of their meaning would therefore be helpful. The header image above offers one way to distinguish between key terms. This may be helpful if you feel your board could benefit from an improved understanding of this central aspect of their governance role.

All incorporated entities need to be able to demonstrate their solvency – their ability to pay all their debts as and when they become due and payable (refer S.95A of the Corporations Act). This is a conformance requirement, and so it’s one of the key metrics all boards should be continuously monitoring. It is also a key focus of scrutiny by independent auditors.

KPIs, Key Metrics and OKRs

Adopting a Key Performance Indicator (KPI) to achieve a certain percentage in revenue growth year on year, or to recruit a certain number of new members/donors, are performance targets. They are not of concern to regulators like ASIC or the ACNC. Such measures may be important, but they do not normally qualify as ‘key metrics‘ (like solvency ratios, member/donor growth, etc.).

Supporting KPIs, key success factors (AKA competitive or strategic ‘posture’) identify the settings required for an organisation to operate effectively in its domain, i.e. what it must do well to achieve its strategic goals e.g. agility, reliability, diversity, and client engagement.

Objective and Key Results (OKR) measures have become popular in some quarters as they separate outcomes-based results (which measure quantifiable outcomes), from effort-based results (which measure the relative success of innovations, projects, or initiatives).

Key result areas (KRAs) may be used by directors when devising the CEO performance plan, otherwise, identification of KRAs is a management function performed by the CEO and other executives for senior staff roles.

‘Objective’ objective assessment

Adopting vague indicators which could only be assessed subjectively would not represent good governance.

While qualitative measures are required for some types of strategic objectives, it should be possible to identify the types of evidence that could objectively be used to determine whether or not, and with what measure of success, a strategic initiative was achieved. An objective (evidence-based) assessment of objective (goal) achievement if you will.

The set of such measures will include both quantitative and qualitative evidence, according to the nature of the matters being evaluated. The selection of methods and measures will also depend on a range of variables, such as the nature of the organisation, its service profile, regulatory obligations, size, age, and governance maturity.

Locus Focus

Unlike hocus pocus, ‘locus’ and ‘focus’ are real words.

Etymonline.com advises that locus is a noun (plural loci), meaning “place, spot, locality,” and that it derives from the Latin locus “a place, spot; appointed place, position; locality, region, country; degree, rank, order; topic, subject”.

The same authority advises that focus too is of Latin origin. It means “point of convergence,” with its Latin origin referring to “hearth, fireplace” (also, figuratively, “home, family”).

‘Modus’ is the third Latin term used in the header chart, meaning the “way in which anything is done” (hence modus operandi).  

The locus of control is a factor in the selection of the right evaluation measures. If the board is responsible for setting strategy and the associated key performance indicators (albeit with advice from management), then they are the locus. If management is responsible for setting goals for a given position, then management is the locus (of control).

Applying Robert Tricker‘s 2X2 corporate governance matrix (illustrated below), the focus of monitoring and evaluation needs to be both be internal and external. It also needs to be performance and conformance related. Depending on which aspect of governance the board is monitoring and evaluating, different types of measures will be suitable.

Your Monitoring and Evaluation Framework

https://tinyurl.com/fnaus7bh