Key Takeaways

• AI in education is moving beyond chatbots. Schools should prepare for AI-powered workflows that support teaching, assessment, and administration—not just standalone chatbot use.
• The focus must shift from AI outputs to student thinking. As AI becomes more capable, schools need to rethink teaching, assessment, and classroom practice to ensure technology supports learning rather than replacing it.
• Success with AI depends on strategy, governance, and people. The schools best placed for 2026/27 will combine clear AI governance with targeted staff development, thoughtful tool selection, and a culture of safe experimentation.

There was a point, not that long ago, when a school could reasonably say it was still thinking about AI.

A leadership team could form a working group. Someone could write a policy. A few enthusiastic teachers could experiment with an AI chatbot. Everyone else could wait to see where this was going.

That position will not survive the coming academic year.

Over the past year I have spent a lot of time with teachers, school leaders, technology leads and people responsible for AI strategy across schools and districts in different parts of the world. What interests me most is rarely the polished story. It is what happens once the conference presentation is over. What worked when students used the tool? What genuinely saved teachers time? What sounded brilliant in theory but fell apart in a classroom?

These questions sit at the heart of The Educators’ AI Guide 2027, a new book edited by Heather Brown and me, with contributions from hundreds of educators and school leaders already doing this work. The book, which I am delighted is supported by Lightspeed Systems, shows what happens when these questions reach real classrooms, leadership teams and students.

The question for the coming school year is no longer whether schools should engage with AI.

Students and teachers already are. The more important question is whether schools are going to approach it deliberately or continue making decisions one problem at a time.

1. The Chatbot Era Is Already Becoming Old News

For a lot of schools, AI still means opening a chatbot, typing a prompt and waiting for something useful to appear. Write me a lesson plan. Create ten quiz questions.

That was the first wave. It is not where the technology is heading.

AI is moving towards connected workflows where one action leads into another. A system might help develop a lesson, create and differentiate the resources, build the assessment and then analyse the resulting work.

Dave Hinrichs and Christie Cloud write about this transition in their chapter, AI Has Moved On. Have Educators? As they put it, “The shift is not simply from one tool to the next. It is from isolated tasks to connected work. “The interesting question is becoming less about whether a teacher can write a clever prompt and more about whether they can use AI intelligently across that chain of work.

This creates an immediate problem for leaders. In the same school you may have one teacher who has barely touched an AI system and another who is quietly building their own tools. A two hour session showing everybody twenty useful prompts looks increasingly inadequate.

Schools need to understand where their people actually are, then help each person move one sensible step forward. There is no sense pretending that everybody needs the same training.

2. We Are Going to Have to Talk Seriously About Thinking

This, for me, is the biggest classroom issue.

AI makes it incredibly easy to produce things. That is useful for adults. It becomes more complicated when the person using it is supposed to be learning how to produce those things themselves. A student can generate an essay without wrestling with the argument or solve a problem without understanding the method. They can produce something that looks remarkably like learning without necessarily doing much learning at all.

In his chapter, The ACTIVE AI Framework, Daren White describes this as the point “where the act of learning is replaced by the act of completing.” That is the risk in a sentence. A finished product may look stronger while the learning beneath it has become weaker.

The danger is that schools respond by turning the whole conversation into one about cheating. I think that would be a mistake. Detection tools will not solve this. Blanket bans will not solve it either. The more useful question is about when AI enters the learning process.

Imagine two students preparing for a debate. The first asks AI to develop the arguments and evidence before exploring the topic. The second develops their own position and tests their reasoning before using AI to challenge it. Both students have used AI. But cognitively they have done completely different things. The second student still owns the thinking.

Samantha Armstrong makes this distinction particularly well in her chapter, AI in the Messy Middle. She writes, “If AI enters before students have a stake in the work, it becomes a shortcut. If it enters after, it becomes a tool.”

Sometimes AI should not be used at all. Sometimes it might be useful for brainstorming or extensive exploration. What matters is that everybody understands which situation they are in and why. Students also need a better mental model of these systems. They are not digital professors waiting to reveal the truth. They generate responses from patterns in data and can sound completely confident while being wrong.

There is an equity issue too. A student with strong knowledge may use AI to extend their learning. A student without that foundation may use the same tool to avoid developing it.

Armstrong offers an important warning: “If we hand them a tool that does the cognitive work, we are not closing a gap. We are widening it.”

3. Assessment Has Reached the Point Where Something Has to Change

Here is a useful exercise for the start of term. Take one of your existing assessments. Give it to an AI model that students can reasonably access. See what happens. If the system can produce a near perfect response in seconds, you have learned something important about the assessment.

Larisa Black gives schools an admirably direct test in her chapter, Shifting Assessments in an AI Enhanced World: “If AI earns 100%, then this assessment probably needs to shift.” That does not mean the subject is obsolete. It does not mean students should stop writing essays. It does mean the final product can no longer be the only evidence we care about. For years, schools have talked about valuing the learning process. AI may finally force us to mean it.

Black argues that this is where portfolios can become far more useful. Rather than simply storing completed pieces of work, “The portfolio becomes a record of thinking, not just a record of answers.”

This does not require every school to redesign assessment from scratch. Start small. Collect the plan as well as the essay. Ask for an earlier paragraph or a short reflection. Have a two minute conversation about the work. These additions make it much harder to separate the product from the thinking that produced it.

There is a strange irony here. AI is creating the assessment problem, but it may also help make better assessment manageable by organising notes, structuring documentation and surfacing patterns for a teacher to review.

The important boundary is obvious, and Osman Aliefendioğlu captures it neatly in his chapter, From 21 Hours to 90 Minutes: “The AI proposes. The teacher decides.”

4. AI Governance Is About to Become Much More Serious.

There was a stage in which the school’s AI policy could basically say, “Do not enter personal data into ChatGPT.” That stage has passed. The governance questions are multiplying.

What information is being shared? Can a teacher require students to use a product? Can parents opt out? Who approves a new tool? Who has access to student conversations? How are unsafe responses reported?

The strongest approach I have encountered is a representative AI group. It should include teachers, leaders, people responsible for safeguarding and data protection, and sceptics. You want people in the room who will ask awkward questions.

Chad Sussex and Sandy Groom Meeks learned this while establishing their district’s AI task force. In their chapter, The Winterset AI Task Force, they write, “While it may be tempting to fill a committee with early adopters, team members who play ‘devil’s advocate’ are invaluable.”

Schools also need a proper process for approving tools. Educational value, ease of use and cost matter. But if a product cannot explain what happens to student data, that should matter more.

Then there is the emerging complexity of AI companions, designed to simulate conversation, friendship and sometimes emotional attachment. Children may use them at home long before a teacher knows the platform exists. Safeguarding conversations with parents need to evolve too.

5. Teachers Are About to Become Software Builders

There are two contradictory things happening in education technology at the moment.

The first is exhausting. There are far too many tools, each claiming it will revolutionise planning, assessment or administration. No teacher can meaningfully evaluate all of them, and they should not try.

Darren Begley writes candidly about this in his chapter, Coping with the Sense of Drowning in New Tools. After trying to keep up with a growing list of AI products, he realised, “I had swapped one list of tasks that was eating up my valuable time for another. I was back at square one.” One of the smartest decisions a school can make this year may be deciding what it is not going to use. Choose a small number of good tools, train people properly and go deeper. Chasing every release creates another form of workload dressed up as innovation.

But something else is happening at exactly the same time. Teachers can increasingly build things themselves.

Until recently, if a teacher wanted software for a specific classroom problem, the answer was tobuy whatever existed, ask the technology team or forget about it. That is changing.Sethi De Clercq explores this shift in Democratisation of Custom Built Tools. In his words, “Software development has become conversational, and the coding language of choice is shifting toward English.”

A teacher can describe a problem and increasingly create a functioning tool without being a traditional programmer. It might be a feedback system, a revision tool or a small application for something the school’s existing system handles badly.

Schools do not have to remain passive consumers. Teachers can become creators. But leaders need safe conditions for that to happen. You do not want staff building tools with sensitive data and no oversight, or governance so restrictive that every idea dies before it can be tested. Give staff safe places to experiment and share what works. People need examples, practice and colleagues they can ask stupid questions without feeling stupid. That is less glamorous than announcing a huge transformation programme. It is also far more likely to work.

This Is the Year Schools Need to Become Intentional

A lot of what happened over the past couple of years was experimentation. Schools tried things. Some worked. Some did not. Teachers explored. Leaders wrote cautious policies. We learned.

The schools that navigate the coming year successfully will know why they are using AI. They will have clear boundaries around data and safeguarding. They will understand when AI strengthens learning and when it weakens it. They will rethink assessment and give staff space to build expertise gradually.

They will also accept that some decisions will be wrong. The technology will continue changing after the decision has been made.

There will not be a perfect moment when somebody finally hands education the definitive AI playbook. We are going to have to build it while the technology is moving.

So start somewhere. Look honestly at where your school is today. Choose one problem worth solving. Put sensible safeguards around it. Try something. Talk to the people affected by it.

Change what does not work. Then move again.

Schools do not need perfect certainty about AI. They need the confidence to make thoughtful decisions without waiting for certainty to arrive.

Ready to Build Your AI Strategy?

The next academic year will demand more than AI policies—it will require clear governance, informed decision-making, and the right technology to support teaching, learning, and safeguarding.

Whether you’re reviewing AI adoption, strengthening data governance, or ensuring new tools align with your safeguarding strategy, Lightspeed Systems can help you move forward with confidence.

Talk to our team to explore how Lightspeed supports schools in building safe, effective AI strategies.