AI Readiness Assessment

Where does AI currently show up inside day-to-day employee work?

AI is rarely used or not used at all Used occasionally by a few employees Used for simple tasks like search or summaries Used regularly across multiple functions Embedded into most daily work activities Primary interface through which work gets done

How frequently do employees independently experiment with AI tools?

Employees rarely experiment with AI tools A few employees test AI occasionally Experimentation happens informally Teams regularly test new AI workflows Experimentation is encouraged organisation-wide Continuous experimentation drives innovation

How are AI prompts typically structured today?

Prompts are random and inconsistent Basic one-line prompts are common Some structured prompting exists Employees use repeatable prompting methods Prompt frameworks are standardised Advanced prompting systems optimise outputs

How connected are AI outputs to actual business deliverables?

AI outputs are rarely used in deliverables Outputs are occasionally referenced Some outputs appear in final work AI outputs regularly contribute to deliverables Deliverables heavily rely on AI assistance AI directly drives production outputs

How dependent are employees on AI for completing work?

Employees do not rely on AI AI is occasionally helpful AI supports some recurring tasks AI is important for productivity AI is critical to execution Work would significantly slow without AI

How consistent is AI usage across different individuals?

Usage differs heavily between individuals Only a few employees use AI consistently Usage patterns are emerging Most teams use AI consistently AI usage is standard across the organisation AI behaviour is systemised organisation-wide

How often are AI tools used beyond simple information retrieval?

AI is mainly used like a search engine Used for simple writing or summaries Used for repetitive productivity tasks Used for workflow assistance Used for decision support and execution AI systems actively operate workflows

How seriously is AI currently viewed inside the organisation?

AI is viewed as unimportant AI is considered experimental Leadership sees moderate potential AI is strategically encouraged AI is considered operationally important AI is viewed as core to future competitiveness

How consistently do employees use AI for recurring tasks?

AI usage is inconsistent for recurring tasks Some employees use AI repeatedly Recurring AI usage habits are forming AI is consistently used for recurring tasks Recurring workflows depend heavily on AI AI autonomously supports recurring operations

How structured are prompting habits across employees?

Prompting habits are unstructured Some employees use basic templates Teams are developing prompting standards Prompting methods are standardised Advanced frameworks are used across teams Prompt optimisation systems evolve continuously

How often do employees reuse prompts or workflows?

Prompts are rarely reused Some prompts are reused informally Reusable workflows are emerging Prompt reuse is common across teams Shared prompt systems exist organisation-wide Dynamic prompt systems optimise automatically

How much productivity improvement has AI created at an individual level?

AI has created little productivity improvement Small productivity gains exist Moderate productivity improvements are visible AI significantly improves productivity Productivity gains are organisation-wide AI fundamentally transforms operational efficiency

How often are AI-generated outputs used directly in work?

AI outputs are rarely used directly Some outputs are reused manually Outputs often support employee work AI outputs are integrated into execution Outputs drive operational workflows AI outputs autonomously power execution

How embedded is AI into writing, research, or analysis workflows?

AI is disconnected from core workflows Used occasionally for research or writing Used regularly within productivity workflows Embedded into recurring execution workflows Operational systems rely on AI support AI continuously orchestrates workflows

How much time savings has AI introduced for employees?

AI creates almost no time savings Minor time savings are visible Moderate time savings exist AI significantly reduces execution time Large-scale operational efficiency exists AI drastically compresses operational timelines

How often do employees refine AI outputs before final delivery?

Employees rarely refine AI outputs Basic editing is common Employees iteratively refine outputs Refinement workflows are structured Collaborative optimisation processes exist Continuous AI-human optimisation loops operate

How integrated is AI into real project execution?

AI is disconnected from project execution AI occasionally assists projects AI contributes to some project tasks AI is embedded into project execution Projects heavily depend on AI collaboration AI systems orchestrate operational execution

How often do employees use AI iteratively rather than one-off prompting?

Employees mainly use one-off prompts Some follow-up prompting occurs Iterative prompting habits are forming Employees regularly iterate with AI Deep refinement workflows exist AI-human iteration continuously optimises outputs

How effectively do employees maintain context across AI interactions?

Context is rarely maintained across sessions Limited continuity exists Employees sometimes preserve context Context retention is common in workflows Persistent operational context exists AI systems continuously learn from organisational context

How much of the execution process involves AI collaboration?

Execution is mostly manual AI occasionally assists execution AI contributes to workflow execution Execution regularly involves AI collaboration AI is deeply embedded into execution AI orchestrates large parts of execution autonomously

How dependent are employees on AI for solving complex problems?

AI is rarely used for complex problems Used occasionally for support AI assists with some complex work AI is important for solving complex problems Complex execution relies heavily on AI AI drives advanced operational intelligence

How integrated are AI outputs into client-facing or operational deliverables?

AI outputs rarely appear in operational work Outputs occasionally support delivery AI contributes to operational deliverables Deliverables consistently integrate AI outputs Operational delivery depends heavily on AI AI autonomously powers operational output creation

How repeatable are AI-assisted execution processes?

AI-assisted execution is inconsistent Some repeatability exists Repeatable workflows are emerging Execution processes are repeatable Systems operate with high consistency Operational execution self-optimises continuously

How effectively do teams combine human review with AI-generated outputs?

Human review is disconnected from AI outputs Basic review processes exist Review workflows are improving Human-AI collaboration is structured Operational review systems are mature AI-human collaboration continuously improves execution quality

How standardised is AI usage across teams?

AI usage is inconsistent across teams Some teams use AI regularly Shared AI behaviours are emerging AI usage is standardised across teams AI systems align operational execution AI behaviour is orchestrated organisation-wide

How often do teams use shared prompts, templates, or playbooks?

Teams rarely share prompts or workflows Some prompt sharing exists informally Shared templates are emerging Teams regularly use shared playbooks Operational systems standardise workflows AI continuously optimises organisational workflows

How embedded is AI into operational workflows and delivery systems?

AI is disconnected from operational workflows AI supports isolated workflows Workflow integration is increasing AI is embedded into operational systems Operations depend heavily on AI coordination AI autonomously orchestrates workflows

How aligned are teams in how they use AI?

Teams use AI differently without alignment Some alignment exists informally Operational alignment is improving Teams are aligned operationally AI systems coordinate execution across teams Organisation-wide AI alignment continuously evolves

How documented are AI workflows across the organisation?

AI workflows are undocumented Some workflows are partially documented Documentation standards are emerging AI workflows are well documented Operational systems maintain workflow governance AI systems continuously update workflow intelligence

How integrated is AI into planning, review, and execution cycles?

AI is disconnected from planning cycles AI occasionally supports planning AI contributes to planning and review AI is integrated into execution cycles Operational systems rely on AI coordination AI continuously optimises organisational planning

How scalable are AI workflows across departments?

AI workflows are difficult to scale Some workflows scale inconsistently Scalable workflows are emerging AI workflows scale effectively across departments Operations scale efficiently through AI systems AI autonomously scales organisational capability

How consistently are outputs generated across teams using AI?

Outputs vary significantly between teams Some output consistency exists Operational consistency is improving AI standardises outputs across teams Operational quality is systemised AI continuously optimises organisational output quality

How much of operational work is currently automated using AI?

Operational work is almost entirely manual Small automations exist AI automations support some workflows Automation is embedded operationally Operational execution heavily depends on automation AI autonomously manages operational systems

How advanced are your AI workflow automations?

AI workflow automations are basic Some workflow automations exist Automation maturity is improving Advanced AI workflows operate consistently Operational automation is highly mature AI systems autonomously optimise automation architecture

How frequently are multi-step AI pipelines used?

Multi-step AI pipelines are rarely used Simple AI sequences exist Pipeline workflows are emerging AI pipelines support operational execution Operational systems rely on orchestrated pipelines AI autonomously coordinates multi-agent systems

How dependent are workflows on human intervention today?

Workflows require constant human intervention Some automation reduces manual effort Human dependency is decreasing AI handles many operational tasks independently Operations scale with limited human intervention AI autonomously governs operational execution

How integrated are AI agents into operational execution?

AI agents are not operationally integrated Basic AI agents are being tested AI agents support limited workflows Agents are embedded into operational execution Operational systems rely on AI agents AI agents autonomously coordinate organisational execution

How effectively are AI systems connected across tools and workflows?

AI systems operate independently Some systems are loosely connected Workflow integrations are improving AI systems are operationally connected Integrated AI systems coordinate execution AI infrastructure autonomously orchestrates operations

How measurable are efficiency gains created through AI automation?

Efficiency gains are difficult to measure Some improvements are visible Efficiency tracking is improving Operational gains are measurable AI significantly improves operational efficiency AI continuously compounds operational performance

How mature is governance around AI automation and risk management?

Governance around AI automation is weak Basic governance exists Governance standards are emerging Operational governance is mature Automation governance is strategically embedded AI autonomously supports governance optimisation

How effectively do AI systems improve over time based on usage?

AI systems rarely improve from usage Some learning mechanisms exist AI improvement processes are emerging AI systems improve operationally over time Continuous learning drives operational advantage AI systems autonomously evolve organisational capability

How much organisational knowledge is retained inside AI systems?

Organisational knowledge is disconnected from AI Some knowledge is captured manually Knowledge integration is improving AI systems retain operational knowledge Knowledge compounds organisation-wide AI continuously evolves institutional intelligence

How scalable is organisational capability through AI?

AI capability is difficult to scale Some scaling improvements exist AI scalability is improving operationally AI significantly expands organisational capability Operations scale efficiently through AI systems AI autonomously compounds organisational scale

How integrated is AI into strategic decision-making?

AI rarely influences strategic decisions AI occasionally supports leadership decisions Strategic AI usage is increasing AI is integrated into decision-making Leadership depends heavily on AI intelligence AI continuously shapes strategic direction

How continuously are workflows optimised through AI insights?

Workflow optimisation is mostly manual AI occasionally identifies improvements Workflow optimisation is improving AI continuously supports operational optimisation Operational systems self-improve through AI insights AI autonomously evolves organisational workflows

How effectively does AI reduce dependency on headcount growth?

Growth depends heavily on hiring more people AI reduces some dependency on headcount Operational leverage is improving AI significantly expands output capacity Operations scale efficiently without proportional hiring AI autonomously compounds organisational leverage

How embedded is AI into long-term operational strategy?

AI is disconnected from long-term strategy Leadership sees future AI potential Strategic AI planning is emerging AI is embedded into operational strategy AI drives long-term organisational transformation AI continuously shapes strategic evolution

How close is your organisation to operating as a truly AI-native business?

The organisation is far from AI-native Some AI-native behaviours are emerging AI maturity is developing steadily The organisation operates with strong AI integration AI is central to operational execution The organisation operates as a truly AI-native business