Whatever you think of the technology, “generative AI” are the words on everyone’s lips. Tech leaders are under pressure from chief executives to deploy the probabilistic prompt-based tool at all costs, while security leaders worry about the implications.
For some, GenAI is an intriguing possibility without a compelling use case. For others, such as Rafee Tarafdar, CTO of Infosys, a global technology services business, this primordial stage in the development of GenAI is exactly the right time to double down on the technology.
While market analysts have begun to question the usefulness of GenAI – with even early cheerleaders such as Goldman Sachs expressing scepticism – Infosys has decided to upskill its entire global workforce of 340,000 people to prepare to use the technology.
“As part of our own AI-first transformation, when we looked at what was required to have an AI-ready workforce we recognised there would be a spectrum of users and impact,” Tarafdar explains. “But when we launched our plan we decided that everybody, irrespective of their seniority, has to become AI-aware.”
To get started, Infosys set out to understand the organisation’s skills landscape. It looked at all tasks and roles and determined what could be automated, what could change with AI and which new skills would be required.
A tailored approach to GenAI training
The company decided that some in its workforce would be consumers of GenAI – for instance, a sales rep using the technology to research a client or a developer who wants to write code faster. This cohort needs to understand how to make the most effective use of the technology, to create useful prompts and incorporate GenAI into their workflows with a critical eye.
Others will create with AI: their training focuses on how to code GenAI products either for Infosys or for its clients. Some roles may be a combination of the two cohorts.
The company has adopted a three-tiered approach in its AI transformation. The first stage is to make everyone “AI-aware”, ensuring that all employees are familiar with the basics. In the second stage, “builders” will be trained to create products using GenAI. These employees need to understand how to work with AI models or APIs: the type of staff tasked with creating AI assistants for wealth advisors, for example, or AI-enabled customer-service bots.
Stage three will focus on “masters”. These employees need a much deeper understanding of GenAI. Masters might specialise in safety – protecting against prompt injections or prompt hijacking – or be subject-matter experts building training models and scrutinising large sets of data for usefulness and quality.
84% of our employees – that’s 270,000 people – are now AI-aware
Clearly, a one-size-fits-all approach would be ineffective. To get around this challenge, Infosys has used its internal training platform, Lex, to create 66 courses on GenAI mapped to each persona. Some courses are designed to help staff become AI-aware, while others are tailored to builders or masters.
The training platform combines different approaches for learning. These include the Socratic method, which prompts users to come to conclusions or answers on their own. The platform also adopts simulations and adaptive learning, tailoring education to the specific requirements of the individual. Hands-on workshops or training sessions are also available for leaders, employees and clients.
Tarafdar says that 84% of Infosys employees – about 270,000 people – are now AI-aware.
“We have a large number that are builders and masters too,” he adds. “Anybody can use this platform any time, and that’s how we’ve been rolling out this change across the company. We’re midway through right now: AI-aware is largely done, but there’s more work to do for the builders and masters.”
How to keep GenAI in check
Infosys must ensure that staff being trained on AI learn how to check against coding biases in its applications. Recent legislation such as the EU’s AI Act, which declares “discriminatory impacts and unfair biases” in the technology to be unlawful, make compliance an important regulatory matter.
To avoid these problems, Infosys weaved its own responsible AI framework into its training programme. This covers explainability – so users of AI understand what occurs under the hood, the kinds of data being used and to what end – as well as ethical and security considerations.
When Infosys began its AI transformation, it established an internal “centre of excellence” to promote the safe and responsible use of AI. It then brought in an external auditor to evaluate its responsible AI processes, before applying for the ISO 42001 standard – a commitment to establishing, implementing, maintaining and continuously improving AI management.
How Infosys tracks its AI progress
To track the programme’s impact, the company collects metrics around daily average users of its AI platforms and the acceptance rate of code created with GenAI.
It also encourages employees to flag issues with AI so the trainees become the trainers. For instance, if an employee notices a poorly automated translation or transcription, they can dispute the offending portion and correct it themselves, helping to teach and fine-tune the AI model.
“Where there are more fundamental issues, engineers look at feedback or disputes,” says Tarafdar. “All of this happens digitally so it becomes a process where they improve the dataset.”
Organisations that have taken a strategic approach and have built the right foundation will deliver value
Employees might baulk at a broad AI programme becoming integral to the company’s daily operations. Genuinely efficient automation has historically put jobs at risk, from the looms of the industrial revolution to self-service checkouts in supermarkets.
This may explain why Infosys CEO Salil Parekh recently denied that any cuts were on the cards owing to GenAI. However, some may struggle to accept that the technology is only here to help people be more productive. Many businesses that have been the loudest advocates for GenAI have also blamed it for recent cuts.
Despite the scepticism, Tarafdar is confident that GenAI is here to stay.
“In my view, the organisations that have taken a strategic approach and built the right foundation – using the right platform, the right data, being responsible by design and having the right use cases – will deliver value,” he says. “I don’t think there’s much of an issue for people who have done those things. Where they’ve just gone with the hype, then there is an issue.”
