Often these days, conversations inevitably turn to the topic of AI. While we should expect this as it has and will continue to transform our world, I can’t help but note the rather disparate takes, understandings and discourse on the matter, even amongst IT professionals. While most of us don’t possess deep academic training on the subject, myself being more of a hobbyist for most of my engineering career, and have spent most of our existence in a world where AI was just a curiosity, I always observe a certain juvenile quality to these conversations, as if the masses were thrust into carrying on an informed conversation on a matter that takes years and years to master.

And so I offer to the reader this tier list of organization AI strategies. These conversations help me realize that the majority of companies are still adjusting to this new world, with most making sincere efforts to appear informed yet still searching for the path to post scarcity AI nirvana.

Aside from drawing parallels between colleagues and companies, it frames the topic of AI in terms of a natural progression from the nature of the change, to level of impact it can have, and what to expect from the next level of transformation, and what will be needed to reach the next level.

I offer these 5 tiers, with a fun culinary spice to them. Tier I contains more points than any of the other tiers. Seeing how all organizations start their journey here, and that most companies are at this level, this is to be expected.

I: Sprinkle

Light opportunistic exploitation of AI solutions

• characterized by ‘sprinkling’ AI on existing solutions and processes.
• strategists generalize ‘AI’ and apply it vaguely, with little understanding of specific AI instances or appropriateness or cost or value
• often, these ‘AI’ strategies are just application of traditional IT/computer solutions mislabeled as AI
• Tier I strategies also claim AI utilization through curation of AI-labeled vendors ,tooling, basic plugins, and integrations.
• Tier I strategies are often broad yet shallow, and lack measurement or KPIs.
• No formal strategy, training, or organizational mandates provisioned nor imposed.
• Tier I strategies are spearheaded by leaders with very little AI fluency or perhaps technology in general, who rely on an assumed instinctual understanding of AI and its value proposition (as an example, contrasting different AI methodologies such as deep learning, neural network, gen AI, LLM, etc, and how these techniques differ in suitability to solving different problems)

II: Stir

Deliberate integration of AI into specific workflows and tools. -Stategists have at least a basic understanding of AI as a field

Vendors and tooling undergo informed analysis before adoption; such integrations feature custom integrations and configurations.

Organizational adoption features basic guidelines and training

Focus on boosts and efficiency is targeted

Changes are still additive rather than transformative

III: Simmer

Deep embedding of AI across multiple functions, with custom solutions and data feedback loops.

• Organizational leaders either possess AI fluency or consult and delegate AI adoption and operations to informed strategies
• Fine-tuned models, internal AI platforms, agentic workflows (AI agents that plan and execute multi-step tasks), and RAG systems.
• Cross-functional governance, data infrastructure investments, and measurable ROI tracking.
• AI influences decisions, optimizes operations, and starts reshaping how work is done.
• Legacy roles and titles are augmented and replaced by AI oriented skillsets.
• The organization is "letting AI simmer" — changes are gradual but pervasive.

IV: Bake

AI is baked into core business processes and products; the company redesigns operations around AI capabilities.

• Enterprise-wide platforms, autonomous agents/swarm systems, predictive analytics at scale, and AI-driven automation of complex workflows.
• Significant talent hiring, ethical frameworks, and cultural shift toward AI fluency.
• New revenue streams or cost structures emerge from AI (e.g., AI-powered products or services).
• AI is no longer a layer — it’s fundamental to how value is created.

V: Feast

AI-native transformation: the entire organization is built or rebuilt around AI as the primary driver.

The organization is now an industry leader thanks to an exponential advantaged realized through AI

Continuous AI-human collaboration and evolution of proprietary AI models