Anyone who answers this question in one sentence is doing you an injustice. Being AI-ready is not a slogan and it is not a purchase. It is three separate bodies of work: legal, technical and cultural. Get all three in place before your first employee starts, and you will do extremely well. Skip any one of them and you will pay for it, in fines, in wasted spend, or in a leadership group that quietly splits in two.
1. Legal: the part with penalties attached
The EU AI Act is already in force, its transparency obligations arrive on 2 August 2026, and penalties reach EUR 35 million or 7 per cent of global turnover. The delayed high-risk deadlines changed none of that.
Concretely, if you use AI in your business, internally or externally, you must be able to show that your employees have been made AI-literate, which in practice means keeping records of who was trained and on what. If you run an AI chatbot on your website, you must tell your customers they are talking to AI. There are further criteria, and there is a governance protocol behind all of it. The days of handing an employee a 20 dollar subscription and calling it done are over. It has to be managed, recorded and documented.
Then GDPR, which is a separate law with separate fines. Being AI-ready here means knowing exactly where your data is processed and being able to prove it. Personal and client data can be processed outside your country, but only with a lawful transfer mechanism and the right contract in place, and your clients need to be told what happens to their information. This is why the tier and the vendor matter: on business and enterprise agreements the provider commits not to train on your content, and European data residency is available as a specific contractual feature you must request by name. Self-hosting removes the question entirely, but almost no normal company can justify the GPUs and the data centre capacity that requires.
2. Technical: readable by people, usable by machines
The technical work is smaller than most vendors want you to believe, and it has four parts. Decide which tools are approved and on which tiers, so nobody is working on a personal account. Know where each of those tools processes data, so the legal section above is answerable. Define access boundaries before any agent touches a system, because an agent can only reach what you connect it to, and those permissions are a governance decision rather than an IT preference.
The fourth part is the one companies miss entirely: your public surfaces have to be readable by machines. AI systems and agents now evaluate your company on behalf of buyers who never visit your website. Structured content, semantic markup and machine-accessible information decide whether you appear in that answer at all. This is measurable, not aesthetic. My own site scores 79 out of 100 on Cloudflare’s agent-readiness assessment, and the gap between a site that scores well and one that does not is invisible to humans and decisive for machines.
3. Cultural: the part that actually changes your company
When you release AI into your company, every employee suddenly has access to the smartest colleague they have ever worked with. Available 24 hours a day, never taking a coffee break, reading a million pages a second, answering any question without judgement.
That changes people. Give it to one person and that person changes. Give it to a team of fifty and that team will never work the same way again, and they will now be visibly different from every other team in your company. Give it to five hundred and the shift is exponential. This is already happening in your organisation, mostly in silence.
Here is the risk nobody warns you about. If you adopt AI as a leader and the rest of your leadership group does not, your leadership style changes and theirs does not. That is a cultural fracture inside the room where decisions get made. The change is for the better, but until you have planned for it, it is heavy and complex. The hardest part of this was never the technology.
Do the strategy in the right order
Before you build an AI strategy to take on your competitor, build the AI strategy to launch it inside your own company. Legal handled. Technical decided. Culture prepared. All of it in place before the first employee starts. Then bring in the counsel that keeps you moving.
Being AI-ready is more than hype. It is critical, and it is entirely achievable when it is done professionally and in the right sequence.
Frequently asked questions
What does it mean for a company to be AI-ready?
Three things, not one. Legal readiness: EU AI Act obligations including employee AI literacy and chatbot transparency, plus GDPR compliance on where data is processed. Technical readiness: approved tools and tiers, known data locations, defined access boundaries for agents, and public content that machines can read. Cultural readiness: a plan for how AI changes how your people and your leadership group work.
What does the EU AI Act require to be AI-ready?
Employees must be made AI-literate, and you should hold records showing it. Customers must be told when they are interacting with AI, such as a website chatbot. Transparency obligations apply from 2 August 2026, with penalties reaching EUR 35 million or 7 per cent of global turnover.
Can we use AI and still comply with GDPR?
Yes. You need to know where the data is processed, hold the right contract with the provider, use a lawful mechanism for any transfer outside your jurisdiction, and inform clients about how their information is handled. Business and enterprise tiers with European data residency make this straightforward. Personal consumer accounts do not.
Where should a company start with becoming AI-ready?
With an internal strategy, before any competitive strategy. Settle the legal obligations, decide the tools, tiers and access boundaries, and plan for the cultural change, all before the first employee begins using AI in daily work.
Thomas Anglero is a Strategic AI Advisor, keynote speaker and author of Intro to Artificial Intelligence. He has delivered over 450 keynotes across 30 countries for organisations including IBM, the WHO, the World Government Summit and the European Commission. He founded the IBM Watson AI Lab for Cancer at the Oslo Cancer Cluster and closed over $500 million in enterprise transformation deals as CTO and Chief Innovation Officer at Cognizant.
If you are leading your organisation through this, I work with a limited number of senior leaders each quarter. Get in touch at Anglero.com.