The problem of graduates viewing AI as cheating is landing squarely in the laps of professional services firms, according to Rob Hillard, CEO of Deloitte’s Asia-Pacific branch, who used a Bloomberg interview this week to argue that universities are sending workers into the labour market with a fundamentally miscalibrated relationship with the technology.
‘Too many are seeing the technology as cheating,’ Hillard said. ‘We have to change that.’ His concern is not philosophical: AI use is a core competency in consulting, and firms like Deloitte are embedding generative and agentic AI into workflows to handle repetitive, data-heavy tasks that once fell to junior staff. Bringing in graduates who treat the technology as ethically suspect creates a friction that the firms themselves must then unpick.
A Policy Gap Driving the Perception Problem
The Gallup and Lumina Foundation survey of around 3,800 students offers some structural explanation for why graduates arrive with that ‘negative perception’, as Hillard described it. Some 42% of respondents said their school discourages AI use, and 11% said the technology is prohibited outright. That reluctance among educators is partly driven by fears of academic dishonesty and by efforts to encourage independent, critical thinking.
Yet the policy picture is patchier than those headline numbers suggest. According to the Lumina Foundation, 52% of students report that at least some of their classes lack clear guidance on specific AI use policies. Students are not simply being told not to use the tools; in many cases, they are being left without any coherent framework at all, which may itself be reinforcing the sense that AI sits outside the bounds of legitimate academic work.
Hillard’s prescription is direct. The only way to prepare workers is by ‘working hands-on with the technology, with seeing how you can get the most effective interface between people and machine,’ he said. Universities, in his view, have been slow to make AI a central part of how students prepare for the workplace, and shifting those perceptions is key to evolving professional practice as the technology itself evolves.
Graduates Viewing AI as Cheating Despite Using It Anyway
The practical reality on campuses cuts sharply against the institutional stance. Despite widespread restrictions, 57% of US college students said they use AI in their coursework at least weekly, and one in five said they use it daily. The gap between policy and behaviour is even more pronounced when examined by institutional environment. Reporting by infoDOCKET on the same Lumina-Gallup data found that 48% of students at schools that actively discourage AI still use it weekly, as do 27% of students at schools where it is prohibited altogether. Students are using the tools regardless; the institutional signal they are absorbing is that doing so is transgressive.
The profile of heavy users is also telling. Gallup found that AI use is higher among students in business, technology and engineering programmes compared with those in other fields of study, precisely the pipeline feeding into firms like Deloitte. Those graduates are already using the tools; the challenge is whether they arrive understanding them as professional instruments or as something to be concealed.
The Workforce Stakes for Professional Services
The stakes for large consulting firms are concrete. Top firms, including Deloitte, are racing to embed AI into their workflows, using the technology to accelerate tasks previously assigned to junior staff. That shift raises questions about how firms develop early-career workers when the training-ground work those workers would have performed is increasingly automated.
Hiring pressure in the sector is real. Recruitment for certain roles, including management consultants, is down. Deloitte’s fellow Big Four firm PwC has cut all entry-level recruitment in the US by a third over the next three years, in part due to ‘the impact of AI’, according to reporting by Business Insider. Against that backdrop, Hillard offered a counter-signal: Deloitte is taking on ‘record numbers of graduates’ and investing more than ever in training them for the work of the future. The qualifier matters. Volume of hiring is one thing; arriving graduates will also need to shed the view that reaching for an AI tool is an ethical breach rather than a professional baseline.