Know exactly how ready your business is for AI
Paloren provides AI readiness consulting that assesses data, systems, people and governance, then hands you a prioritised roadmap. Engagements from USD 8,000.
Leaders who need a clear picture of AI readiness before committing budget to projects.
Paloren delivers AI readiness consulting through a structured assessment of your data, systems, people and governance. Engagements start at USD 8,000, run two to three weeks, and end with a scorecard, a risk register and a prioritised roadmap you can act on immediately.
AI readiness consulting is a structured review of whether your organisation can adopt AI without stalling. A consultant examines the data you hold, the systems that hold it, the skills your people carry and the controls that govern how information moves.
The goal is not to sell a tool. The goal is to find where AI would genuinely work and where it would fail quietly. That origin matters. An engagement typically covers six dimensions: data quality and access, technology stack, workflow maturity, team capability, governance and risk, and leadership alignment.
Each dimension is scored, evidence is collected from real systems rather than assumptions, and gaps are ranked by how much they would block a first project. You finish with a scorecard you can defend in a board meeting and a list of fixes ordered by impact.
Nothing in the assessment requires you to commit to implementation afterwards, although many organisations choose to continue.
The work, made concrete
Six scored dimensions from data to leadership
Evidence gathered from live systems, not assumptions
A scorecard and ranked gap list you can defend
Most AI failures trace back to conditions that existed before the first prompt was written. Models inherit the quality of the data beneath them. Agents inherit the chaos of the workflows around them.
When a company skips readiness work, it usually discovers the problems mid-build, which turns a fixed-scope project into an open-ended repair job. A readiness assessment moves that discovery forward, while changes are still cheap.
It answers practical questions: can staff actually reach the data a use case needs, does anyone own data quality today, which tools already overlap, and where would an AI agent meet a process that has no defined owner.
Paloren combines implementation, workflow design and practical team training. Large organisations rarely lack technology. They lack clarity about what they already own. Readiness work produces that clarity in weeks rather than months.
It also protects budget. Companies that assess first tend to sequence projects in an order that funds itself, because early wins release the resources that later, larger builds require.
| Dimension | What is examined | Common gaps found |
|---|---|---|
| Data quality and access | Where information lives, how clean it is, who can reach it | Fragmented sources and permission blocks |
| Technology stack | Overlap, integration points and tool sprawl | Platforms bought department by department |
| Workflow maturity | Processes traced end to end for handoffs and owners | Unowned steps and undocumented logic |
| Team capability | Current skills, training gaps and adoption attitudes | Skills concentrated in too few hands |
| Governance and risk | Policies, privacy handling, security posture, approval rights | Policies that drift from real practice |
| Leadership alignment | Shared goals for AI across the executive team | Divergent views on priorities |
Every dimension is scored and combined into one overall readiness rating.
Source: Paloren published service ranges
| Factor | How it changes scope | Effect on cost or timeline |
|---|---|---|
| Number of systems in scope | Each additional platform adds audit and inventory work | Raises cost toward the upper end |
| Interviews required | More business units mean more structured conversations | Extends the schedule within the window |
| Depth of governance review | Regulated environments need deeper policy and security checks | Increases both effort and price |
| Pilot use case scoping | Scoping a first project adds roadmap detail | Adds days to the final week |
| Executive reporting format | Board-ready materials need extra drafting | Minor effect on total fee |
Readiness engagements start at USD 8,000 and run two to three weeks.
Source: Paloren published service ranges
The work, made concrete
Problems surface while fixes are still cheap
Budget is sequenced so early wins fund later builds
Clarity replaces guesswork about existing systems
The assessment looks at six areas, and none of them sit only in the technology department. Data comes first. Consultants map where information lives, how clean it is, who can access it and whether permissions would block an AI system from doing useful work.
Technology follows: the current stack is reviewed for overlap, integration points and the friction that appears when tools were bought department by department. Workflows are the third area.
Processes are traced end to end so the assessment can see where handoffs break and where automation would compound existing confusion rather than remove it. People come next, because capability determines adoption.
The review covers current skills, training gaps and the attitudes that will shape whether staff use new systems or quietly ignore them. Governance is the fifth area: policies, security posture, privacy handling and the decision rights that decide who may approve an AI system.
Leadership alignment closes the loop. If executives hold different views about what AI should achieve, that disagreement surfaces now, while it costs a conversation instead of a project.
Each area receives a score, and the scores combine into an overall readiness rating.
The work, made concrete
Data, stack, workflows, people, governance and leadership
Processes traced end to end for handoff failures
Every area scored and combined into one rating
An engagement runs over two to three weeks and follows a fixed sequence. Week one opens with a briefing session where leadership describes the outcomes they want from AI, followed by a technical audit of data sources, platforms and integration points.
The Paloren team inventories systems directly rather than relying on documentation, because documentation in most companies drifts from reality within months. Interviews form the second thread.
Structured conversations with staff across functions reveal how work actually happens, which spreadsheets hold critical logic and which processes exist in name only.
Governance review runs in parallel: privacy handling, access controls, security posture and approval pathways are checked against the demands AI systems will place on them.
Findings are then consolidated into a scorecard across the six assessment areas, with each gap given a severity rating and an estimated effort to fix. The engagement closes with an executive readout where the results are presented, debated and turned into an agreed action list.
Throughout, the team works remotely with your existing tools, so there is no software to install and no disruption to daily operations.
The work, made concrete
Two to three weeks, briefing to executive readout
Direct system inventory instead of trusting documentation
Remote delivery with no disruption to operations
Deliverables are concrete documents, not a slide deck of opinions. The core output is a readiness scorecard that rates each of the six areas and explains the reasoning behind every rating.
Alongside it sits a data and systems inventory: a single list of what you own, where it lives, who can reach it and what condition it is in. The risk and governance register captures every issue found during the review, from access controls that are too loose to approval pathways that would slow an AI project to a halt.
Each entry carries a severity rating so leadership can see which items block progress and which merely need tidying. The prioritised roadmap turns findings into a sequence.
Use cases are ranked by readiness, impact and effort, and each one is scoped with an indicative budget band and timeline drawn from Paloren's standard ranges. Finally, the executive readout gives leadership a shared, evidence-based picture of where the organisation stands.
Every deliverable is written to be used: the inventory feeds integration planning, the register feeds governance work, and the roadmap feeds the decision about which project to run first.
The work, made concrete
Readiness scorecard with reasoning behind every rating
Risk and governance register with severity ratings
Roadmap with indicative budgets and timelines per use case
Readiness engagements at Paloren start at USD 8,000 and run over two to three weeks. That figure covers the full assessment: briefing, technical audit, interviews, governance review, scorecard and executive readout.
Cost moves with scope rather than with time alone. A company with a handful of core systems and a single region sits at the lower end. A group with multiple business units, overlapping platforms and strict regulatory obligations needs more interviews and a deeper governance review, which raises the figure.
The price is deliberately small relative to what it protects. First AI projects across the wider service set range from USD 25,000 to USD 100,000, and company brain builds reach USD 60,000 to USD 150,000.
Spending a fraction of that on readiness before committing reduces the chance of funding a project the organisation cannot support. There are no hidden extras in the engagement.
The fee is fixed once scope is agreed, the timeline is stated up front, and the deliverables listed on this page are included. If the assessment reveals that readiness is already high, the roadmap will say so, and you can proceed to implementation with confidence.
The work, made concrete
From USD 8,000 over two to three weeks
Fixed fee agreed once scope is confirmed
Price scales with systems, interviews and governance depth
Three situations call for readiness work before anything else. The first is the organisation that has tried AI tools in isolated pockets and now wants to scale, but cannot tell which foundations are missing.
Scattered experiments leave behind fragmented data, shadow tools and no governance, and an assessment maps that landscape honestly. The second is the company planning a significant investment, such as a company brain or a fleet of AI agents, where leadership wants evidence that the ground will hold before releasing budget.
A readiness rating gives the board something concrete to weigh. The third is the business that has been asked hard questions by regulators, partners or its own people about how AI is governed, and needs a documented position fast.
The assessment produces that documentation as a by-product of the roadmap. Size matters less than intent. The Paloren team has worked inside environments as demanding as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC, and the method adapts to whatever scale it meets.
What stays constant is the sequence: understand the ground, score it honestly, then build.
The work, made concrete
Scaling companies with scattered AI experiments
Boards weighing a major first investment
Businesses that need documented governance quickly
The assessment is designed as a doorway, not a dead end. Findings map directly onto the Paloren service set, so each gap identified has an obvious next move. If data is fragmented across systems, workflow automation and integrations, priced from USD 15,000 over three to eight weeks, usually comes first to join the pipes.
If a company brain is the ambition, the inventory and governance register produced during readiness become the inputs that shorten its eight to twelve week build. Where the roadmap points to customer-facing automation, chatbots from USD 20,000 or AI voice agents from USD 25,000 inherit the workflow maps already drawn.
CRM work with AI, ranging from USD 20,000 to USD 80,000, depends heavily on data quality findings from the assessment. Team AI training closes the loop on the capability gaps the interviews expose.
Nothing is forced. Some organisations complete readiness work, act on the fixes internally and return months later. Others move straight from the executive readout into a strategy engagement, priced from USD 12,000, to turn the roadmap into a full programme. The assessment stands on its own either way.
The work, made concrete
Findings map to a named service for every gap
Readiness outputs shorten later project timelines
Continue with strategy or act internally, both valid
Preparation is light, but a little effort up front multiplies the value of the two to three weeks. Gather access to the systems that hold operational data: the CRM, the analytics stack, the document stores and any data warehouse.
Read-only access is enough for the audit. Nominate a small set of interviewees across functions, ideally people who touch core processes daily rather than only managers who oversee them.
Honest answers during interviews matter more than polished ones; the assessment is not an audit of individuals, and the most useful findings often come from descriptions of workarounds.
Collect whatever policy documents exist on data handling, privacy and security, even if they are out of date, because gaps between the written policy and actual practice are themselves findings.
Finally, have leadership articulate in one sentence what they want AI to achieve this year. That sentence anchors the prioritisation of the roadmap. The Paloren team handles the rest: scheduling, the audit itself, interview design, scoring and the executive readout.
Most organisations can be fully prepared within a week of agreeing scope.
The work, made concrete
Read-only access to core systems
Interviewees who do the work daily
Existing policies, even outdated ones
Leadership defines the outcomes AI should deliver, and the team confirms scope, access and the interview schedule.
Data sources, platforms and integration points are inventoried directly, with condition and access mapped for each system.
Staff conversations reveal how work really happens while privacy, security and approval pathways are checked in parallel.
Findings across all six dimensions are rated for severity and combined into the overall readiness scorecard.
Results are presented to leadership, debated openly and converted into an agreed, prioritised action list.
| Dimension | What is examined | Common gaps found |
|---|---|---|
| Data quality and access | Where information lives, how clean it is, who can reach it | Fragmented sources and permission blocks |
| Technology stack | Overlap, integration points and tool sprawl | Platforms bought department by department |
| Workflow maturity | Processes traced end to end for handoffs and owners | Unowned steps and undocumented logic |
| Team capability | Current skills, training gaps and adoption attitudes | Skills concentrated in too few hands |
| Governance and risk | Policies, privacy handling, security posture, approval rights | Policies that drift from real practice |
| Leadership alignment | Shared goals for AI across the executive team | Divergent views on priorities |
Every dimension is scored and combined into one overall readiness rating.
Paloren published service ranges
| Factor | How it changes scope | Effect on cost or timeline |
|---|---|---|
| Number of systems in scope | Each additional platform adds audit and inventory work | Raises cost toward the upper end |
| Interviews required | More business units mean more structured conversations | Extends the schedule within the window |
| Depth of governance review | Regulated environments need deeper policy and security checks | Increases both effort and price |
| Pilot use case scoping | Scoping a first project adds roadmap detail | Adds days to the final week |
| Executive reporting format | Board-ready materials need extra drafting | Minor effect on total fee |
Readiness engagements start at USD 8,000 and run two to three weeks.
Readiness scorecard covering all six dimensions
Data and systems inventory with access and condition
Risk and governance register with severity ratings
Prioritised roadmap with indicative budgets and timelines
Executive readout presentation with agreed actions
Signal → Synthesis → System → Scale
Find where intelligence creates value.
Understand the business to identify and prioritize the opportunities with the greatest measurable impact.
Translate complexity into a clear design.
Bring together the people, workflows, data, and technology to define how intelligence should work.
Turn the design into a working capability.
Build the solution that embeds intelligence into how work and decisions happen.
Compound what works.
Measure impact, optimize performance, maintain reliability, and unlock greater leverage.
From signal to scale.
S4 structures the readiness review so every finding is grounded in evidence from real systems, not assumptions. Data, workflows, governance and team capability are each scored and ranked by impact.
| Step | Stage | What it changes |
|---|---|---|
| 01 | Signal | Collect the data inventory, system list, current data-quality issues, workflow owners and who can actually reach each source. |
| 02 | Synthesis | Score the six dimensions, map overlapping tools, and rank gaps by how much each would block a first AI project. |
| 03 | System | Test access paths against real systems, trace governance controls, and verify whether a candidate use case has a defined process owner. |
| 04 | Scale | Deliver the scorecard and prioritised fix list, assign ownership for data quality, and sequence projects so early wins fund the next ones. |
AI readiness consulting evaluates whether an organisation has the data, systems, skills and governance to adopt AI successfully. Consultants audit technology, interview staff, review policies and score each area against a framework.
The output is a scorecard, a risk register and a roadmap showing which AI projects are realistic now, which need preparation first, and which should wait.
Most engagements run two to three weeks from briefing to executive readout. Week one covers the briefing and technical audit. Interviews and governance review follow in parallel.
Scoring, roadmap drafting and the final readout complete the schedule. Scope affects the timeline: more systems and more business units extend the window, but Paloren states the exact schedule before work begins.
Readiness engagements start at USD 8,000 and complete within two to three weeks. The fee covers the full assessment, including the audit, interviews, governance review, scorecard and executive readout.
Cost rises with the number of systems in scope, the interviews needed across business units and the depth of governance review required by regulated environments. The price is fixed once scope is agreed.
Yes, and often most of all. Scattered tool adoption creates fragmented data, shadow systems and ungoverned practices that block scaling. The assessment maps that landscape, shows which experiments rest on solid ground and identifies the gaps that would undermine larger builds.
Duplicated tools and unmaintained datasets are among the most common findings, and both are cheap to fix once named.
You leave with a scorecard, an inventory, a risk register and a prioritised roadmap. From there you can act on the fixes internally, move into a Paloren strategy engagement to build a full programme, or begin a first project such as automation or a company brain.
The roadmap sequences options with indicative budgets so the decision is informed.
Leadership sets direction in the opening briefing and receives the executive readout at the close. Between those points, the team needs interviewees across functions who touch core processes daily, plus a coordinator who can arrange system access and scheduling.
Technical staff support the audit. In total, expect a handful of hours per person across the two to three weeks.
Yes. Paloren serves businesses worldwide and runs engagements remotely with your existing tools. Read-only access is sufficient for the technical audit, interviews happen by video at times that suit each participant, and nothing needs installing.
Remote delivery keeps costs down and lets the assessment cover multiple locations and business units without travel or disruption to daily operations.
Readiness assesses where you stand today; strategy decides where to go next. The assessment produces a scorecard, a risk register and a roadmap of viable use cases.
A strategy engagement, priced from USD 12,000 over three to four weeks, builds on those findings to define priorities, sequencing and investment across a longer horizon. Many organisations run both in sequence.
Request a scope call. Paloren will confirm what the assessment covers for your systems, agree a fixed fee from USD 8,000 and schedule the briefing.
How ready is your business for AI?
Book a readiness assessment
