Artificial intelligence (AI) is steadily making its way into roles across all industries and teams. Rather than taking people’s jobs, this new tech is changing them, requiring a large shift in skill sets, role remits, and how talent is developed and hired.
Here’s everything I’ve noticed in my role as Practice Manager for Technology at Robert Half during the tech industry’s rapid evolution within the last 18 months, and how hiring strategies, succession planning, and tech talent can adapt to stay competitive.
The evolution of AI-related roles and AI skills in tech
There's a growing demand for roles such as machine learning engineers, product managers, and project managers, but with a key distinction — tech employers are specifically looking for candidates who have applied AI in their projects, portfolios, or products. These are currently the most common AI-related roles my colleagues and I have come across.
Robert Half has done a huge amount of work with tech employers, building out DevOps and site reliability engineering teams to scale their technical estate. Three or four years ago, there weren't any AI-related requirements within those roles. Over the last 12 to 18 months, we're starting to see that those jobs now have a heavy AI element to them.
The Robert Half tech hiring team also regularly work with fintechs and businesses that are building platforms for clients or selling software as a service (SaaS) to customers. Those roles in the product space are now starting to incorporate AI within them, too.
Read: 5 Roles created by the rise of AI
Why all professionals should consider learning AI skills
It's fairly common for talent to worry that AI will replace them, and I think that, throughout history, new technologies have continually emerged to test the workforce. But there's never going to be a scenario in which millions of people in the UK are left unemployed because AI has taken everyone's jobs. It's just not going to happen. But we still have to adapt.
You can start by finding ways to incorporate AI chatbots or AI tools more regularly into your everyday life — get ChatGPT or Google Gemini on your phone and PC while you're doing your day-to-day work to increase your fluency in it. Incorporating it into everyday life is critical.
For tech talent, having the ability to be more cross-functional will also make you incredibly valuable to the company, especially as tech now integrates with every team across every department. The people who can communicate effectively, are commercially minded, and understand the operational side of a business while incorporating technical aspects, are the ones who are likely to secure new opportunities in the future.
Cultural fit and soft skill capabilities are also hugely important. You're now getting leaders from other departments coming into the final stages of an interview process to talk to potential technology professionals before any decisions are made. These leaders recognise that a new technology hire could be integral to their team, and the ability to communicate and work cohesively is more important than it's ever been. And that's only going to continue.
My colleagues and I have seen concern at a senior leadership level around analysing the future of the business, and who they've got at the junior levels that could potentially be the leaders of the future within the organisation, and what skill sets these successors possess. The best tech talent in the pipeline will be those who can learn quickly, communicate effectively with senior stakeholders, and collaborate across cross-functional divisions. This mix of skills is what will make you stand out from others in the marketplace.
Read: Expert panel – 5 key ways generative AI is impacting businesses
Adapting hiring strategies to meet demand for AI and AI automation skills
Tech employers are evolving their hiring strategies to keep pace with the demand for AI skills. An effective way to achieve this is to hire for potential, not just credentials. Here at Robert Half, we do quite a lot of work with biotech companies and businesses doing AI-related technical work in the world of science.
Historically, these businesses would have only hired individuals who were exceptionally academically accomplished, having attended top universities, earned degrees, and possibly even PhDs in scientific fields related to AI. That would have been the bare minimum, and if that wasn't on a CV, that person wouldn't have gotten an opportunity.
Nowadays, tech employers are opening their minds up. They're looking at people's GitHub accounts, personal interests, and self-upskilling capabilities. There's more interest in people moving from other departments after upskilling themselves through courses. AI's evolution has forced business leaders to be more open-minded regarding unconventional career journeys.
Read: Rise of AI – How to prepare your business for the future of AI
Avoiding common misconceptions about AI skills in tech talent
Some people still believe that AI requires a PhD or an advanced research background, which is obviously very helpful and can add a huge amount of value, but that's not always necessary nowadays. There's now a huge wave of young, enthusiastic talent who are not going to university for three years, doing a PhD, or signing themselves up to £100k worth of debt, but are still just as passionate about things like AI and deep technical solutions.
Another common misconception is that AI projects fail due to poor technology; however, tech recruiters like myself have noticed that it's often more to do with a lack of soft skills, collaboration, or effective change management. This shows me that people aren't necessarily clear on what AI really is, what it means, and how it works.
In my experience, the tech talent or AI-users who can communicate complexity more simply are the people who will be more successful and more valued in a business because AI and automation can be confusing if you're not technical. It's easy to get lost in jargon and heavily over-technical terminology.
The tech professionals who level up the best (and likely secure more seniority and commercial roles within businesses) are the people who can put complex terminology into layperson's terms to deliver it to the masses in a digestible way.
Understanding the shift from ‘building tools’ to ‘orchestrating tools’
We've seen an evolution in our tech recruitment team here in London — we've done a considerable amount of work with software engineers and developers, and those job titles seem to be shifting to 'AI integrator' or 'automation enabler.' We're seeing a growing demand for advanced skills in areas such as APIs and platforms like Azure Machine Learning and Vertex AI. These new requirements signal significant shifts in tech talent recruitment from traditional building tools to orchestrating tools.
My colleagues and I regularly work with fintechs that utilise AI within the platforms they build for their clients. APIs are a key skill set required to implement that technology within their clients' environments. Requests for API skills have grown considerably. Having said that, you could be the most knowledgeable person in AI and have strong API skills, but if you can't communicate effectively, manage clients, own a piece of work, and be commercial with clients, and have that skill set alongside the technical skill set, it just won't work.
My team and I had a very recent example with a startup company. They're a regtech business that is only two years old but scaling quickly. They've asked us to help them find implementation consultants to put their cloud-based platform, which has a lot of AI sitting within it, into their clients' environments. We’ve noticed that there are a lot of technical people out there with all the required knowledge, but the only ones who were progressing were those who could effectively communicate and demonstrate great client management skills.
It all comes back to having the capability to communicate, implement, and manage clients, as well as the technical capability — you can't have one or the other. So, while AI is improving and taking elements of people's roles, the fundamentals of what humans do to implement, own, and manage that process can't be replicated by technology.
Future-proofing your career in an AI-driven era
Cultivating an AI-centric mindset is essential. I'd also recommend taking charge of your own upskilling — there are so many different online courses available. LinkedIn is a great place to start. Start with small projects and certifications, and begin with small online tutorials, whether they are free or have a minimal cost.
Professionals who invest in lifelong learning and adaptability are the ones who progress the fastest because AI may be the hot topic now, but fast forward 10 years, and it'll be something else. So, continuous improvement and adaptability are key and need to become an ingrained habit.
From a hiring perspective, people who have a growth mindset, that self-driven up-skilling, often outdo those with formal credentials. If you can demonstrate a genuine desire to progress and take on more responsibility, you could give yourself a real value-add in your career. Now is an opportunity for people to make big leaps and bounds in their careers, if that is truly what they want to do.
