Enterprise AI Transformation
AI Transformation Strategy & Roadmap
Most organisations can run an AI pilot. Very few can scale one. The gap is rarely the model. It’s the plan around it. Which problems to solve first, who owns them, what has to change in the way people work, and how it all gets paid for. We build that plan with you, and we make sure it holds up once it meets the business.
Enterprise AI Transformation:
Business AI Modeling
We don’t just implement AI. We transform how enterprises THINK, DECIDE, & OPERATE.
Most organizations can pilot AI. Very few can scale it. AI Transformation is where strategy, technology, and people converge i.e. a disciplined journey from experimentation to embedded, enterprise-grade intelligence.
At Agentics, we help organisations move beyond POCs, models, & dashboards by redesigning technology, processes, and behaviours for AI to become a core operating capability, not a side initiative. We partner with leaders to embed AI into how work gets done, redesign processes around intelligence, and ensure adoption sticks.
Your AI Transformation Journey
Step 1 → Enterprise AI Readiness & Maturity Assessment
Step 2 → Everything AI to identify high-impact use cases and build solutions
Step 3 → AI Transformation to scale, embed, and sustain AI across the enterprise
Ready to move from AI pilots to Enterprise Transformation?
Let’s build an AI-native organization, Together.
— The short answer
What is an AI transformation strategy?
It’s the plan for making AI part of how your company runs, not a side project. It sets out which use cases to pursue and in what order, the operating model and governance to run them, the data and technology they need, and the business case that funds them. A good one fits on a page. A useful one turns into a roadmap your teams can actually execute.
— Where this fits
Assess. Plan. Build.
01
Assess
Find out where you stand and where AI will pay back first.
Readiness assessment →
You are here
02
Plan
Turn those findings into a strategy, an operating model and a funded roadmap.
03
Build and scale
Put agents into production, then grow from one use case to many.
Multi-agent solutions →
Already know your gaps? You can start here. We’ll fold a lighter diagnostic into the first weeks instead of running a full assessment.
How we think about it
The model is 10% of the work
BCG put a number on something every practitioner already knew. To get value from AI at scale, about 10% of the effort goes into the algorithms, 20% into technology and data, and 70% into people and processes.
Most AI vendors sell you the 10%. Some help with the 20%. Almost nobody stays for the 70%, which is exactly where pilots go to die. Our strategy work covers all three, and our roadmaps budget time and money the same way.
10%
Models and agents
The right intelligence for each job
20%
Data and technology
A foundation agents can work on
70%
People and process
Where transformation actually happens. Workflows, operating model, governance, skills and adoption.
Rule of thumb from BCG.
Models and agents
Choose the right intelligence for the job
The model matters less than people think, but picking the wrong one is still expensive. We decide where you need a single agent, where a team of agents should run a whole workflow, and where plain automation is enough.
Use case portfolio
A ranked list of what to build, scored on value, effort, risk and data readiness.
Agent design
Which tasks agents own, which they assist with, and where a person signs off.
Build, buy or reuse
Which needs a custom build, which an off-the-shelf tool covers, and where our own products fit.
Data and technology
A foundation agents can actually work on
Agents need clean data to read and systems they can act on. We design the data and technology foundation that lets AI run in production, securely, without ripping out what already works.
Data foundation
Where data lives, who owns it and what needs fixing first, including the documents and emails no system reads today.
Architecture blueprint
How agents connect to your ERP, CRM and cloud, and which integrations come first.
Platform choice
One place to build, run and govern every agent. Cortex, our enterprise AI agent platform, is one option we put on the table.
Data literacy
Self-service analytics and training so teams can use what the data tells them.
People and process
Where transformation actually happens
Most AI initiatives don’t fail because the model is weak. They fail because nobody changed how the work gets done, or nobody used the output. This is the part of the plan we spend the most time on.
Process
Process discovery
We map how work really flows, using process mining and real usage data, not the version in the policy manual.
Workflow redesign
We rebuild key workflows so agents trigger, decide and act where they should, and hand off to people where judgment counts.
Cross-functional design
Finance, operations, supply chain, sales, service and HR, each with its own priorities and metrics.
Feedback loops
Every workflow gets a way to measure results and improve over time.
People
AI operating model
Who owns AI, who funds it, who signs off. Centre of excellence, roles and decision rights.
Governance and responsible AI
Policies, risk tiers and controls that satisfy your board and the EU AI Act.
AI fluency
Role-based learning, from the executive team to the front line.
Adoption design
We find out why people might resist, and design around it from day one.
Trust and explainability
Confidence scores, audit trails and clear escalation paths so people trust what the agents do.
Incentives
KPIs and rewards that pay people for using AI well, not for working around it.
— Deliverables
What lands on your desk
An AI strategy on a page, tied to your business goals
A ranked use case portfolio with value, effort and risk for each
A target operating model, with roles, decision rights and an AI centre of excellence
An architecture and data blueprint
A governance framework aligned to the EU AI Act
A business case with costs, benefits and payback per wave
A 12 to 36 month roadmap in waves, with milestones, owners and KPIs
A change and adoption plan
A board-ready summary you can take into the next budget round
— How it runs
Three stages, built around decisions
STAGE 01
Align
We interview leadership and function heads, agree what success means and set the ambition.
You decide
The goals
STAGE 02
Design
We build the use case portfolio, operating model, architecture and governance with your teams.
You decide
The priorities
STAGE 03
Commit
We turn it into a costed roadmap and business case, and present it to your leadership or board.
You decide
What to fund
Each stage ends on a decision that’s yours to make. If the numbers don’t support a use case, we say so before it goes in the plan.
Agentic AI platform
Cortex. The operating system for AI-native enterprises.
Cortex is our enterprise AI agent and app builder platform. It connects your existing systems so agents can work across them, with one registry and one audit trail for every agent you run.
— What happens next
From roadmap to results
Agentic AI multi-agent solutions
Build the first use cases on the roadmap.
AI governance and EU AI Act
Put the controls in place before you scale.
Enterprise technology modernisation
Get the foundation ready.
Value accelerator services
Get more from what’s already live.
AI transformation strategy, answered
What is an AI transformation strategy?
It is the plan for making AI part of how your company runs. It covers which use cases to pursue and in what order, the operating model and governance to run them, the data and technology they need, and the business case that funds them.
What should an AI transformation roadmap include?
A ranked list of use cases, delivered in waves. Each wave has an owner, a budget, milestones, KPIs and a payback estimate. A good roadmap also shows dependencies, like data fixes or platform work, and the change and training plan that goes with each wave.
What is the 10 20 70 rule for AI?
It is a rule of thumb popularised by BCG. About 10% of the effort to scale AI goes into algorithms, 20% into technology and data, and 70% into people and processes. The point is simple. Most of the work, and most of the risk, sits outside the technology.
What is the difference between an AI enabled and an AI native enterprise?
An AI enabled company adds AI tools to work designed before AI existed. An AI native company redesigns the work so agents own whole steps and people handle judgment and accountability. A quick test. If the AI disappeared tomorrow, would you just be slower, or would core workflows stop?
Do we need a readiness assessment before building a strategy?
It helps, but it isn't required. If you already know your gaps, we fold a lighter diagnostic into the first weeks of strategy work. If you don't, the assessment gives the strategy a firmer base and usually saves time later.
How long until we see ROI from AI?
We plan for measurable ROI from the first use cases within 6 to 12 months. Quick wins on high volume, repetitive work can pay back sooner. Enterprise wide change across many functions takes longer, often 12 to 24 months, and the roadmap shows payback wave by wave.
How do you calculate ROI on AI transformation?
ROI equals net benefit minus total AI cost, divided by total AI cost. Benefits include cost savings, revenue gains, productivity and reduced risk. Costs include build, data, infrastructure, training and running costs. Set a baseline before you start, or you have nothing to measure against.
How do you move AI from pilot to production?
Pick pilots with a clear owner and a measurable outcome. Before scaling, fix the basics. Data quality, monitoring, security and governance. Then roll out in waves, one process or market at a time, measuring as you go. Budget for training and change, not just technology.
How do we get started?
Book a discovery call. Tell us where you are and what your board is asking for, and we’ll tell you honestly what a strategy and roadmap would look like for you.
Ready to turn AI pilots into a plan?
Tell us where you are and what the board is asking for. We’ll tell you honestly what a strategy and roadmap would look like for your business, and what it would take.
