The changing world of Tech - Part 2: Generative AI
In the first instalment of this two-part blog, I focused on the Metaverse, and what it means to the business world in which we are operating as HR professionals. This time I am going to focus on the related topic of Artificial Intelligence (AI), specifically Generative AI.
What is Generative AI?
According to the world's most broadly adopted cloud service, AWS, “Generative AI is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. It is powered by large models that are pre-trained on vast amounts of data and commonly referred to as foundation models (FMs).”
These foundation models are learning algorithms with vast data analytics training sets taken from the internet - a mine of deep learning capable of creating new and original content, new customer experiences and driving productivity. Some of the key companies developing in this space are OpenAI, Hugging Face, Cohere, Anthropic and, as you might expect, Alphabet (Google) and Microsoft.
The potential of machine learning
Whereas the Metaverse and more immersive technologies are more abstract and difficult to grasp, Generative AI is more clear-cut and accessible. OpenAI’s most recent release CPT-4 is easy to sign up for online and requires no implementation or training. Employees are already using it to perform quick-fire research, create marketing copy and create presentations. The more it is used, the more comprehensive it becomes because it is, quite literally, machine learning: the more queries it makes, the more information it accesses and the greater number of intelligent responses it is capable of.
When applied to business, Generative AI can be incredibly interesting. One of the UK’s leading energy providers, Octopus, has been piloting AI in its contact centre for months. Writing in The Times, CEO Greg Jackson stated that AI had been doing the work of 250 people. By integrating the technology with existing systems and processes, Octopus had used AI to respond to customer enquiries, with checks and balances in place to vet the output. "Emails written by AI delivered 80% customer satisfaction — comfortably better than the 65% achieved by skilled, trained people," Jackson wrote.
In Law and Professional Services, AI is being applied to perform some of the heavy-lifting tasks associated with trawling through archives and files. Law firm Allen & Overy, for example, announced in February that Open AI’s legal product Harvey will “empower more than 3,500 of A&O’s lawyers across 43 offices operating in multiple languages with the ability to generate and access legal content with unmatched efficiency, quality and intelligence.”
In Professional Services, PricewaterhouseCoopers announced in April that it plans to invest 1 billion dollars over the next three years, working with Microsoft and OpenAI to automate aspects of its tax, audit and consulting services.
Human vs Machine
So, what does this mean for employees? On the face of it, it looks bleak with machines taking jobs that humans have been doing perfectly well up to this point. But the future may paint a brighter picture than that. Firstly, the mass uptake of AI within businesses will require tech skills, programme management and project management to either integrate with existing technology or build in-house capability. Ongoing, it will also require roles in training and management. And for those organisations that produce and sell software as a service, it will also create a new workstream to enable AI within that software. This is just the start.
Challenges to ponder
With the inevitable avalanche of content created by AI comes familiar dangers: plagiarism, the sharing of sensitive information, and the use of information to inform decisions which may not always be correct. Having tested the concept of prompts to develop a workshop on a particular subject, Chat-GPT created the full workshop outline in less than a minute. These are now set to become boilerplate templates and are likely to lack the creativity and engagement of workshops benefiting from the ‘human touch’.
For HR there will certainly be new policy requirements required governing the intentional and unintentional passing-on of information. Policies will need to dictate when and how AI can and should be used for work purposes. Only by doing this will employees have clarity around the sharing of personal information and IP. Policing all of this will be a challenge and already some organisations are going as far as approving output before it passes a firewall.
As organisations reinvent their operating models to leverage Generative AI, inevitably they will need to adapt internal workflows, supply chain processes and productivity output. This, in turn, will impact on their people and raise questions in Organisational Design. How many roles could be made redundant? How will new roles be conceived? Where will their value lie alongside the technology? How many people will need to be recruited and trained to manage the systems company-wide, or within each functional area? Only with time can we answer these questions, but they will require a lot of thought and careful consideration.
More insight from Sarah Lardner