Will Terminator 2 AI robots take our jobs? Part 1
The leading conversation in tech right now is AI, and how to capitalize on its potential. So what skills are actually needed?
In Silicon Valley, for example, they are fighting between themselves for the best AI Engineers, with acqui-hires also reported, with the FANGS acquiring startups for the technical teams.
AI is not yet replacing jobs but we expect AI to become a normal part of most roles, with talent expected to use it to complement existing daily tasks.
Bank of America released a report asking 150 of its Analysts who cover 3000 companies if AI will be a net creator or eliminator of jobs? The analysts were evenly split.
This suggests the future will be more about harnessing these new technologies to enhance and improve productivity, than how to deal with Terminator 2 style robots taking our jobs.
It’s less replace, more embrace.
AI skills in demand - UK
Machine Learning
Artificial Intelligence
Neural Networks
Natural Language Processing
Generative AI
Robotics
Visual Image Recognition
AI jobs in demand - UK
Software Engineering
System Engineering
Data Analyst
Data Engineer
Data Scientist
Cloud Architect
Research Scientist
AI will help Sales and Marketing increase automation, productivity and speed, so it’s no wonder we have seen demand in non technical roles like Sales, Marketing. Product and Ops with AI sector experience desired.
Most popular non-tech roles requesting AI sector experience
Sales (selling AI software)
Marketing (marketing AI software)
Product (building AI software products)
Operations (Building AI companies, partnering with technical CEOs)
Sectors leading in AI hiring
Banks
Big tech
AI scaleups
Healthcare
Management Consulting
We asked Per Larsen - ex Apple and currently building AI solutions - for his take on the AI talent industry and the future of AI as a whole.
At this stage, most management teams have limited expertise on how AI can be applied to their business and industry. Once a company decides on an AI strategy, they typically hire data engineers and developers.
Meanwhile, some are already dismissing AI as hype because they haven’t seen industry-specific breakthroughs. These companies could face serious trouble if their competitors are quicker to adopt and educate themselves on AI.
AI’s impact on jobs and operations will be profound, especially for companies that lag behind or invest in the wrong solutions.
We also spoke to Gareth Thomas - CTO for PeakData (AI scaleup), who shared his views on the latest AI hiring trends. Gareth is also the Co Host of www.tech-captains.com - a really great podcast which we can highly recommend. We asked Gareth to briefly outline the current AI landscape and why Generative AI is different to what came before.
There seems to be a high level of excitement from Venture capital and Big Tech around GenAI right now and this has rippled into some feverish hiring.
It would seem there are perhaps 3 groups hired into AI:
1. Base Model Engineers with recent experience working on AI/ML projects
2. Then there are the engineers that are building and integrating existing or 3rd party models
3. Data Analytics/Scientists with experience working on AI/ML projects
Gareth also said:
“I think the boundaries between data analysts, scientists, and engineers are becoming more fluid. Many data analytics roles are now blending with machine learning and AI engineering, requiring a more diverse set of technical and analytical skills. People will need to adapt to more AI-centric tools and workflows, focusing more on interpretation, strategy, and the ethics of how they are used”
For data analytics already there is a big impact. Data analysts spend a lot of time cleaning data to make sense of it, often writing simple code to help. A lot of this can now be automated with GenAI down to writing reports for senior management, but I think it will become important for this role to understand the legal and ethical implications.
At the “coal-face” (engineers integrating this into end-user products) the rise of prompt engineering will cause a role to grow somewhere between the data scientists and the engineers. A lot of regular engineers hate writing prompts whereas data scientists get involved with the design of these features to ensure the returned data is as accurate as possible.
What are your thoughts on AI, and how will AI and associated talent be integrated into businesses? Get in touch to join the conversation.