Big Shifts in the Data Analytics & AI Sector
Amrop’s Digital Practice Team has deep technology and digital knowledge, combining functional and sector experience. We leverage our own digital tools and systems to offer a robust sector focused approach, where the Practice Team members form powerful sub-groups based on their in-depth expertise in various digital sub-sectors.
We invited David Bell, Digital & Technology Partner at Amrop UK and a member of the AI, ML, and Data Analytics sub-sector, to share his insights on the advances and convergence the industry is experiencing and the shifts in the style of working it requires from both data analysts and CIOs. Here's what he said:
“The balance in the Data Analytics sector is shifting. Lots of businesses have had numerous data scientists doing modeling, reporting, and other types of heavy-lifting work, but with the increase in AI, it’s become possible to remove much of the repetitive, less compelling aspects of it.
The fact is that AI in many areas can now be more efficient and capable than the data scientists which have been doing the work so far. It doesn’t mean we need fewer data scientists – it means that they can be reassigned to do more challenging, more value-added work. There is no front-end value-add to the situation where lots of large organizations, like banks, have got hundreds of people churning out reports and where there is inefficient communication between departments. As AI becomes more prevalent, it presents an opportunity for the data teams, with proper tooling, to add considerable value. The ecosystem is evolving and there will be people who may struggle to embrace this more challenging environment; on one level the jobs will become more interesting, but the types of jobs will change too.
This, of course, also has a knock-on effect on business users. They are able to operate with the data regardless of the fact that they might lack data and analytics experience and maturity. That’s because the AI tools now are much more intuitive and user-friendly, much more accessible than they used to be. While AI used to be the domain of IT professionals only, now lots of people (Sales, Marketing, Operations) are using AI or RPA without even realizing it – they can just assume that the systems are working a lot better.
This shift has affected leadership too. When it comes to Data Analytics and AI the CIO or CDO will need to be operating on a higher level because the people on their team will be in more value-add roles. They’ll have analysts operating at a higher level because of the tools they have available, they’ll be able to work more independently. There will be the next generation of CIOs who will have naturally evolved as their functions evolve, and they’ll need to be continuously refreshing their knowledge and upskilling themselves to keep up with the people they’re working with.
There was a period when CIOs were reporting to CFOs – IT was a cost to the business, whereas now it’s not just facilitating the business, but also has a value-add function and needs to be at a peer-level with the rest of the C-suite. If the organization still places IT within this structure now, it is likely that potential hires will be less excited about the prospect, as it signals to them that the organization still considers IT as a cost and not a value-add. But what they’d like to do is to use the technology fully to enable the business.
Within AI everything is converging into one practice, one division within the organization, meaning that the breadth of the responsibility of the CIO/CDO is also growing. Organizations are becoming more and more aware of AI and ML, and many are close to reaching the efficiency tipping point due to the many sophisticated tools available.”
Globally Amrop has a strong Digital Practice Group with AI, ML, and Analytics specialists with extensive experience in undertaking global searches working cross-functionally, and on Board and C-level appointments.
To find out more please contact Amrop!