Digital Maturity in the AI Era: Assessment, Workflow and Human Judgement
- Gratitude Worldwide
- May 11
- 4 min read
This article discusses Jisc’s digital maturity assessment, its implications for AI-era workflows, and the importance of human judgement in higher education.
A timely shared structure for conversation
Last week, Jisc produced a new digital maturity assessment for UK higher education, designed to help institutions build a clearer picture of their organisational digital capability.
Where are we now?
Where are the strengths, gaps and risks?
Where might future investment or action be best placed?
It offers a timely shared structure for conversation, not just within digital teams, but across senior leadership, governance, academic practice, professional services, and the people trying to make practical changes in complex institutional conditions.
Universities are responding to a multitude of pressures - generative AI, financial constraints, legacy systems, changing student expectations, evolving teaching practices, staff workload, data questions, platform decisions and the constant need to do more with less.
In this kind of environment, it's easy to look for quick fixes.
A new tool.
A revised policy.
A workflow fix.
A pilot.
A procurement process.
A working group.
Another layer of guidance.
All of these may be helpful, but without a clear enough view of the current state, they can also add more complexity to systems that are already overwhelmed.
This is where Jisc’s framing is valuable.
Digital maturity and AI assessment - beyond tools and policies
Digital maturity isn't measured by how many tools an institution uses. It is reflected in the shared understanding, confidence, evidence and coherence needed to make good decisions about technology - a distinction that is especially pertinent for assessment and feedback.
AI has made academic integrity more visible, but it has also brought older questions into sharper focus.
What is this assessment trying to evidence?
How do students show judgement, process and responsibility?
Where are staff losing time to avoidable friction?
Where are workflows too dependent on local workarounds or hidden knowledge?
Where can technology genuinely reduce pressure?
Where does human judgement need to remain visible, protected and well supported?
How do policies translate into marking, moderation, feedback, student guidance and platform use?
These are not questions that can be answered by policy alone. They sit across assessment design, workflow, systems, governance, staff development and institutional culture.
A university may have an AI policy and still have uncertainty at the point of marking.
It may have a platform in place and still have inconsistent workflows.
It may have good intentions around feedback and still have processes that make timely, meaningful feedback difficult to deliver.
It may ask staff to exercise careful judgement amid unclear handoffs, duplicate checks, and fragmented guidance.
Wasted friction, useful effort and human judgement
This is why I keep returning to the distinction between wasted friction and useful effort.
Wasted friction is the duplicated work, manual workarounds, unclear ownership, awkward platform steps, or processes that only one person understands.
Useful effort is the human involvement that gives assessment its educational value: judgement, interpretation, feedback, moderation, dialogue, academic standards, care and responsibility.
Successful progress will make the useful effort easier, not remove human involvement, and that's where digital maturity and AI-era assessment connect for me.
For institutions to make confident decisions about AI, assessment tools or workflow redesign, they need a full picture of what is actually happening now.
Where is the evidence strong?
Where is trust fragile?
Where is the process unclear?
Where are staff absorbing invisible workload?
Where are students receiving mixed messages?
Where is the system working despite the workflow, rather than because of it?
A more coherent path
Jisc’s assessment is helpful because it invites institutions to step back from isolated initiatives and build a broader organisational view as a basis for better prioritisation, stronger conversations and more coherent action.
This kind of clarity can help universities avoid two major pitfalls...
Tool-first transformation, where technology is expected to compensate for unclear process.
Policy-first reassurance, where a statement exists centrally but staff and students are still left working out what it means in practice.
Both can create the appearance of progress without necessarily improving the conditions for learning, trust or sustainable work.
This path may be slower at the beginning, but it tends to lead to more stable systems, better assessment and feedback, and practical solutions that avoid overloading the humans doing the work:
Understand the current state.
Identify the real sources of friction.
Protect the forms of human effort that have educational value.
Make decisions with the people who will need to live with the change.
Then redesign, pilot or procure from a clearer place.
Iterate.
This is the work I'm increasingly focused on through Gratitude Worldwide: helping universities review assessment, feedback, moderation and AI-era workflows in ways that protect evidence of learning, human judgement and staff capacity.
Not every institution needs a large transformation programme. Sometimes the most constructive first step is a focused diagnostic, a senior-level briefing, a workflow review, or a clearer map of where the risks and opportunities actually sit.
If your university is reviewing assessment, feedback or AI-era workflow risk, I can help you identify a useful starting point.
Whatever the process, the principle is the same.
Do it with care.
Do it together.
Make it workable.
Jisc’s new digital maturity assessment feels like a helpful contribution to that wider conversation, and a good prompt for universities to ask not only how digitally mature they are, but what kind of digital maturity they are trying to build.
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