The Human+AI Maturity Framework (HAIM)

S Singh
Jul 20
5 min read

This framework outlines how organizations evolve in their AI capabilities through three distinct tiers, reflecting sophistication, autonomy, and collaboration between humans and AI systems. Each tier builds upon the previous one, emphasizing both technical infrastructure and organizational readiness.

Introduction

Like mountaineers ascending to new heights, organizations. must navigate their AI journey with careful preparation, proper equipment, and growing expertise.

The “The Human+AI Maturity Framework(HAIM) “ provides a three-stage ascent model that guides organizations from foundational AI adoption to peak autonomous intelligence.

Each stage represents a different altitude of AI capability, assessed through-

GEAR framework: Guidance, Elevation, Adaptability, and Resilience.

This tracks how teams develop navigation skills, reach new capability heights, respond to changing conditions, and build robust systems as they climb toward AI mastery.

The Three Stages of AI Ascent

Stage 1: Base Camp (Guided AI Pathways)

“Learning to navigate with a map and compass”

At Base Camp, organizations establish their AI foundation through carefully mapped, predetermined routes. Teams follow explicit pathways with clear waypoints, focusing on well-traveled terrain that covers the majority of operational needs.

Guidance: Teams learn fundamental AI navigation skills. They understand model capabilities, recognize when to call for backup, and collaborate to chart automation routes.

Both technical and non-technical team members work together to map these guided pathways, gaining hands-on experience with AI’s terrain and boundaries. They discover how AI can handle routine navigation tasks like document classification, data extraction, and content summarization, building confidence to explore new routes.

Elevation: AI capability is intentionally limited to specific waypoints within larger operational routes. The AI cannot deviate from predetermined paths. If it encounters unclear terrain or low-confidence situations, it automatically signals for human guidance. It serves as a reliable compass, not an independent guide.

Adaptability: Routes are fixed and predictable. Teams focus on perfecting known pathways rather than exploring new terrain. This limitation is intentional. Organizations must master basic navigation before attempting more challenging ascents.

Resilience: Trust is built through complete route visibility. Every decision point is mapped and explainable. Teams can confidently trace how choices were made and understand why AI requested human intervention. This transparency eliminates uncertainty and encourages further exploration.

Behind the scenes, technical teams establish critical infrastructure: APIs, data pipelines, monitoring systems, model integrations, and logging.

The human-guided feedback creates a learning loop that improves current routes and identifies unexplored terrain for future ascents.

Stage 2: Advanced Camp (Adaptive AI Navigation)

“Learning to navigate with experience and flexible planning”

Organizations ready for Advanced Camp can deploy AI guides within established expeditions to handle unexpected terrain and challenging conditions.

Previous routes continue operating, but now AI guides dynamically navigate obstacles that fall outside traditional mapped pathways.

Guidance: Teams advance fro following predetermined routes to working with AI guides who can make real-time navigation decisions. They develop advanced mountaineering skills including risk assessment, equipment selection, weather monitoring, and. advanced route-finding techniques.

Through continued collaboration, they master complex expedition planning and learn sophisticated guidance patterns like situational awareness and multistep reasoning.

Elevation: AI gains significant autonomy through dynamic route planning and equipment selection. For uncharted terrain, an AI guide receives expedition context and pre-approved gear, dynamically creating plans to overcome obstacles.

but this autonomy operates within defined expedition boundaries, with human expedition leaders maintaining safe operations.

Adaptability: The system can now respond to changing conditions: weather shifts, route blockages, equipment failures. It does this by replanning and adapting. AI guides evaluate multiple route options and select optimal paths based on current conditions and expedition goals.

Resilience: Trust grows as teams see AI guides successfully handle complex terrain and safety systems prove effective by correctly escalating dangerous situations.

Human feedback on guide decisions is recorded, creating a knowledge-rich learning system.

Infrastructure becomes more sophisticated with safety systems, specialized equipment, weather monitoring, route databases, and hazard detection.

A powerful learning loop emerges: human-approved route plans are saved and reused for similar terrain, and when patterns repeat frequently, successful approaches become standard expedition procedures.

Stage 3: Summit (Autonomous AI Expedition Leadership)

“Mastering independent exploration of uncharted territory”

Having developed systems to make AI guidance reliable, teams are prepared to deploy fully autonomous AI expedition leaders.

This represents complete AI autonomy, where leaders orchestrate entire expeditions on-demand to tackle novel/complex/multi-domain, or unprecedented challenges.

Guidance: Teams master the most advanced AI mountaineering capabilities, learning to

define success metrics

design validation systems
build comprehensive scenario datasets
trace AI decision-making
troubleshoot complex situations
run controlled experiments
provide meaningful feedback
implement comprehensive monitoring

This represents peak AI expertise within the organization.

Elevation: AI achieves full autonomy by breaking down complex objectives, selecting and coordinating equipment and team members, reflecting on and adjusting expedition plans, and evaluating various approach options using AI-powered assessment techniques. Leaders can orchestrate complete expeditions dynamically, adapting to unprecedented challenges.

Adaptability: The system excels at handling novel terrain, unexpected conditions, and multi-domain challenges. AI leaders can pivot strategies, reallocate resources, and explore alternative approaches in real-time based on emerging conditions and opportunities.

Resilience: Teams become cautiously optimistic. They recognize impressive potential while acknowledging vulnerability in extreme conditions.

Trust is reinforced through robust monitoring, validation systems, escalation protocols, and structured feedback mechanisms.

Infrastructure reaches maximum sophistication with comprehensive evaluation systems, advanced monitoring and tracking tools, multi-leader coordination systems, context-aware logging, extensive planning and experimentation tools, and detailed performance dashboards.

The learning loop explores multiple expedition approaches simultaneously and logs which ones succeed. Confidence is estimated by checking how often independent approaches converge. When they diverge or confidence drops below thresholds, situations are automatically escalated for human review.

Here is an example-

Supply Chain Expedition

Base Camp: Fixed inventory monitoring routes. AI tracks stock levels, triggers reorder alerts, generates standard reports following predetermined schedules and thresholds.

Advanced Camp: AI guides navigate supply disruptions by assessing alternative suppliers, evaluating transportation options, and proposing contingency plans, with human expedition leaders making final decisions.

Summit: Autonomous leaders orchestrate entire supply chain optimization. They predict disruptions, dynamically reallocate resources, negotiate with suppliers, and implement end-to-end solutions while adapting to global market changes

Like experienced mountaineers, organizations that master each stage develop the confidence and capability to tackle increasingly challenging terrain.

The future belongs not to those who simply deploy AI tools, but to those who learn to navigate the AI landscape with skill, wisdom, and collaborative expertise.