How edtech can help universities support staff and use AI to drive efficiencies in HE

Staff support in HE market map, by Emerge Education.

We’re building our annual list of the top emerging edtech companies in higher education for 2024, in collaboration with our Higher Education Edtech advisory board which is convened in partnership with Jisc and chaired by Mary Curnock Cook, CBE. As we do this, we’re diving into the trends and opportunities for innovation along each step of the learner journey → from student recruitment and enrolment to student experience, teaching and learning, assessment and graduate employability.

In this third article, we’ll dig into the potential for edtech startups to help universities find efficiencies and streamline administrative burdens during these tough times, with a particular focus on supporting academic, research and professional services staff. (We’ll focus more on teaching support in the next piece.)

The student journey in higher education.

Read on for:

• Challenges, trends and opportunities, including our predictions for the transformative impact of genAI
• Views from sector experts, plus tips for founders
• A mini-market map of key players and top emerging startups in this space

Keywords: lecturers, academics, research, professors, university staff, admin, professional services

💡 Why it matters

A digital revolution could provide research, teaching and administrative staff working in HE with more of one vanishingly rare resource: time.

This is one of the key findings from recent research by EY, based on focus group discussions among teaching faculty and professional staff, as well as interviews with senior leaders from universities around the world to discover what they want from digital transformation.

Overstretched administrative staff are still bogged down by mundane and repetitive manual tasks — many of which can be automated — while teaching staff spend unnecessary time on low-value tasks, such as data entry. By automating key processes, implementing joined-up systems that allow for better data sharing and analytics, and utilising generative AI, universities can develop more effective and efficient operations that are built for the people who use them.

🏈 State of play

• Much has been said about the paradigm shift achieved by academic staff during the Covid-19 pandemic to redesign teaching, learning and assessment. Less has been said about the parallel efforts of professional services staff whose work was vital to other aspects of the student experience — pivoting timetables, swivelling student support and more. Perceptions linger of an ‘us and them’ culture within academia. Administrators often fear that they might be targeted as ‘first for the chop’ in times of financial crisis.
• Yet the curious fact remains that in higher ed, it takes more workers to educate a given number of students today than it did one or two generations ago. That’s the opposite of what we have seen in other fields and industries. Between 1976 and 2018, full-time administrators and other professionals employed by institutions in the US increased by 164% and 452%, respectively. Meanwhile, the number of full-time faculty increased by only 92%, marginally outpacing student enrollment which grew by 78%. Three universities — the California Institute of Technology, Duke University and the University of California at San Diego — actually have more non-faculty employees on campus than students.
• So it’s perhaps no surprise that a 2023 McKinsey report on the economic potential of generative AI placed higher education among the top five industries likely to benefit the most from generative AI — and not just for teaching, learning and assessment, but also wider productivity. AI can assist institutions in transforming and improving the student life cycle — from recruitment to alumni engagement — across domains such as operations, marketing and information management like data integration, data quality and data security.
• Staff need to be taken on this journey. Jisc’s most recent survey of professional services staff found only 21% agreed that they were given an assessment of their digital skills and training needs, and only 26% were given the time to explore new digital skills and approaches. Just as importantly, however, 88% reported that technology allows them to work in a way that’s convenient to them, and 83% said it helps them to make good progress with their work. There is more openness to digital innovation than stereotypes of the sector would suggest.
• Similarly, Jisc’s HE teaching staff report reveals teaching staff also need better support to make the most of technology. Only 16% agreed that they were given an assessment of their digital skills and training needs, and again 16% agreed they were given time to explore new digital skills and training approaches.

🚨 Challenges

• Implementation, implementation, implementation. The biggest challenge is getting beyond a great edtech tool in principle and one in action. A long legacy of infrastructure pileup to unwind within universities means it is much harder and more expensive to successfully put in place an enterprise-level workflow solution that has cross-cutting efficiency impact. So many HE institutions have struggled to get behind pilot stages because they were not adequately prepared and resourced for the integration challenges into their (often not very well structured) tech stacks — so openness and honesty about these challenges is somewhere startups could really help their own mission.
• Universities struggle to understand the art of the possible — what success in this area would even look like — which makes it a tough point to sell into. Limited resources are therefore not the only barrier to success: there is lack of understanding across the sector. Often, there’s lots of engagement with individual pilot projects and pockets of innovative practice, but because universities are very devolved in their organisational structure (which makes for very devolved systems), there is resistance when you push to scale strategically.
• “How much are we expected to do with limited available resources?” is a question that echoes time and again in discussions among academic colleagues. There is an epidemic of poor mental health among HE professionals in the UK. Around 20% of university staff meet the threshold for probable depression or anxiety, according to a 2021 study. Staff were working around the clock throughout the pandemic, forced to adopt many new identities, from graphic designers to videographers, alongside their traditional teaching and research roles. Staff need time, space and opportunity to respond.

🔥 Trends

• Many universities are currently undergoing massive rollbacks, after the pandemic years were something of a wild west: proliferating pilots, installations everywhere, inconsistent software licence maintenance and no centralisation. The rollback is having a chilling effect. Even where staff do want to push forward with AI tools, such as automated minute-taking in meetings, this is sometimes being refused. Centralisation is challenging for startups because it means the route to early adopters and proof of concept will become tougher.
• While AI has already revolutionised learning and teaching, fully realising its potential demands a collaborative effort between academics and professional services to jointly steer new pedagogies and develop a flexible infrastructure to underpin personalised learning journeys. Above all, this requires working together towards technological understanding as a perpetual journey, not a one-off training session.

🌍 Key players

42 startups mapped so far

Staff support in HE market map, by Emerge Education.

🔭 Who is getting ahead?

The University of Virginia is one institution that has begun using technology to free up administrators’ time. In partnership with EY, the university has developed an AI-driven virtual HR assistant, CavBot, to welcome new staff. CavBot answers employee queries and helps new hires to complete onboarding tasks, including filling in forms and applying for security badges or parking permits.

This is one of the areas where AI has made significant inroads over the past year, in the form of chatbots. In 2020, Gartner predicted that AI would accelerate the adoption of analytics within higher education and enhance its impact. In Gartner’s 2020 CIO survey, 16% of respondents reported that they had invested in AI chatbots. One year later that figure had almost doubled to 30%. Chatbots have reached an adoption inflection point in HE; it will soon be one of many expected ‘multi experience’ interaction channels for students, faculty and staff. Another example of how AI can help universities improve operational efficiencies is a modern campus network that enables AI-driven Wi-Fi, as the University of Reading has done.

There is a huge array of examples of digital transformation around the sector — you can read more in Jisc’s report, digital strategies in UK higher education: making digital mainstream.

🔮 Predictions

• Admin isn’t sexy, but this is an easy win to save universities money and prove your value. Administrative areas have mushroomed over time into gargantuan processes, with increasing complexity and increased reporting and compliance requirements. Universities have got lots of problems in organisation management, from basic productivity wins such as recording and summarising the minutes of meetings to more complex areas such as coordinating the high (and rising) number of students on individual learning support plans. In the future there will be increased competition between HE and private providers requiring investment in quality student experience, making these admin tools that underpin the learning experience even more important.
• Using AI as part of research is controversial, but there is undoubted potential and plenty of low-hanging fruit. For example, researchers can use generative AI tools to improve the readability of their writing, or to generate plain-language summaries of new journal articles which could feed into regular email roundups for university communications teams. For those working with funding organisations, generative AI can tackle menial tasks such as a first-pass review of funding proposals, checking that they comply with basic submission guidelines. All this would free up time for relationship-building work such as coaching and mentoring.
• Helping staff of all kinds to feel empowered will be crucial to the success of any digital transformation. Some universities have digital champions in each department who act as early adopters and work cross-departmentally to solve common issues. Others have incorporated digital learning into their performance and promotions processes, creating career incentives for those who embrace technology, or build digital skills programmes into their faculty onboarding processes. All of this should be underpinned by ensuring systems and tools are easy to use, and providing accessible, empathetic training and incentives.

🎯 Opportunities for startups

GenAI engines of opportunity for universities

In this category, we see particular opportunities for AI-driven solutions that offer:

• Teaching employees how to use software to enable them to be more productive → Problem: Most SaaS tools are only used in limited ways by the majority of their users. Solution: Includes teaching no-code skills and also how to use sophisticated software.
• AI-powered enterprise knowledge search → Problem: Organisations have a huge amount of internal knowledge that is hard to tap into and find. Solution: Easier ways to discover and apply information within organisations.
• AI-powered second brain → Problem: We constantly come across new information and struggle to retain it. Solution: Better capturing and processing of things you read/come across and helping you apply it in your day to day. One big feature of this would be AI-powered automated tagging of the things you capture.
• Improving access to academic knowledge → Problem: Academic knowledge is hidden away in complicated papers. Solution: Processes and tools that make it more accessible and approachable and personalised.

💎 Tips for founders

• Know a university’s strengths — and identify their blind spots. Before thinking about presenting your product, understand the areas where universities have historically been strong, such as scholarship and teaching. You can certainly enhance these areas, but there are better ways to position your products with universities if you are to become indispensable. Impactful partnerships occur when you can offer something that the university lacks. This could be where the strengths of your product or service overlap with their weaknesses, or where your product or service could bring something completely new to the table. Can you identify an area that lies neither in universities’ strengths nor weaknesses but in their blind spot? Can you find untapped value in the ecosystem that institutions have not yet considered? Administration is a gold mine here.
• Build collaborative teams across partnerships, by taking a relationship-first approach. Most institutional leaders still have relatively limited understanding of the edtech space and see risk everywhere — they are looking for someone who can reassure them. Universities often look for providers with a team that can understand how universities actually work, with people who have empathy and understanding of the challenges that others are facing, so an edtech vendor or partner who has people with education backgrounds can make a big difference. At the same time, find people within the university who understand edtech and what deployments look like. There are plenty of partnerships where that person exists within the university but for some reason they’ve not been part of the project.
• Identify the right decision-makers. You may get an introduction to an institution but this could be many steps removed from an institution’s actual decision-makers or influencers. Here’s Jessica Wang, SVP of Operations at 2U, on the two-step process for navigating the complex hierarchies in HE:

1. Map the terrain

The first aspect to focus on is understanding the decision-making stakeholders and process within a given university structure. Unlike corporates, where it is easier to pinpoint who to sell to, universities have a federated decision-making process, typically featuring a multitude of stakeholders. You should be aware of the following stakeholders:

• Innovation head: start by identifying if there is someone in the institution charged with innovation or bringing new technologies on board. They can be a useful entry point but their reach may be limited.
• Provost or dean: they may have decision-making power, but it might be restricted to a department, school or a specific programme within the university.
• Faculty: They may have a say in the decision-making process. Sometimes, the process might even come down to a vote, which can affect timelines.
• Legal and financial offices: these are often centralised and must be navigated separately.
• Non-traditional entities: some universities have arms that are more focused on customers and end users that are not within the traditional university space eg executive education.

2. Navigate the landscape

After you’ve mapped out the decision-making landscape, it’s time to understand the dynamics between these stakeholders. For Jessica, whiteboarding these relationships has been a helpful tactic to create a visual guide to the internal workings of a university. Within your stakeholders, you should identify the following:

• Most resistant: identify the individual who is most resistant to your offering. Knowing the objections in advance can help you prepare your pitch more effectively.
• Least resistant: find the person for whom your product will solve the most significant problem. They can be your biggest ally in moving your project forward.
• Influencers: these aren’t the decision-makers but they have the power to sway opinion. Get them on board to create a ripple effect in your favour and influence the most resistant stakeholders.

Mapping the internal decision-making landscape of universities enables founders to strategically position their edtech solutions. By identifying key stakeholders, their influence and resistance level, founders can secure contracts more effectively while gaining the broad acceptance required for a successful long-term partnership.

• Mitigate competitive fears and active network effects. Open up channels of communication among your university partners to mitigate the perception of competition. Demonstrate the mutual benefits of participating in a larger network to pivot their viewpoint from competitors to collaborators. When universities recognise the shared value, network effects (and fear of missing out) take over. This not only makes it easier to onboard new partners but also strengthens the value proposition for your existing ones, keeping the growth loop in motion.

Read more in our PMF Academy deep dive: Building successful university partnerships.

🔗 Read on

• Student and staff wellbeing in higher education — Jisc/Emerge Education report (2021)
• How can edtech address some of the greatest challenges facing HE leaders — Jisc/Emerge Education report (2023)
• Edtech 20:20 vision: the top 40 emerging companies for higher education in 2023
• Part 1 in this series → How startups can support universities with recruitment, applications and enrollment
• Part 2 in this series → Startups for student success: how technology can help universities create a stellar student experience

Read more news, views and research from the only fund backed by the world’s leading education entrepreneurs, in Emerge Edtech Insights.

📣 Call to action

We are now building our list of the top emerging edtech companies in HE in 2024.

👇 If you have seen an exciting company in this space, please tell us in the comments 👇

Our list analyses 100s of companies operating worldwide, using public and private data — it is crowdsourced, and voted on by our Higher Education edtech advisory board, led by Mary Curnock Cook.

Please share companies you think we should consider in comments 👇 and join us on 27 June to discover who has made the final list!

🙏 Thanks

At Emerge, we are on the look-out for companies (existing and new) that will shape the future of learning in higher education over the coming decade.

If you are a founder building a business addressing any of these challenges in HE, we want to hear from you. Our mission is to invest in and support these entrepreneurs right from the early stage.

So if you are looking for your first cheque funding do apply to us here: https://lnkd.in/eWi_9J5U . We look at everything as we believe in democratising access to funding (just as much as we believe in democratising access to education and skills).

Emerge is a community-powered seed fund home to practical guidance for founders building the future of learning and work. Since 2014, we have invested in more than 80 companies in the space, including Unibuddy, Cadmus, Engageli and Mentor Collective.

Emerge Education welcomes inquiries from new investors and founders. For more information, visit emerge.education or email hello@emerge.education, and sign up for our newsletter here.

Thank you for reading… I would hugely appreciate some claps 👏 and shares 🙌 so that others can find it!

Nic