In the blink of an eye, AI has become a reality from science fiction. But unlike in science fiction, in reality, humans are not prepared for this world infused with AI. A recent ISACA survey indicated that 40% of organizations offer no AI training at all. It also found that 32% say training is limited to staff who work in tech-related positions—highly limiting given AI’s unlimited scope. The technology is well on its way to becoming akin to a utility, like electricity, water or even internet connectivity.
Managing risk will require a deep understanding of the technologies involved, calling for a deeper technical skilling and reskilling for not only technical staff but also others involved in the decision making process when it comes to the adoption of AI.
In the Indian context, AI adoption has received a fillip with the recent launch of 14,000 GPUs on the IndiaAI Compute Portal at a mere Rs 67 per GPU hour by Union Electronics and IT Minister Ashwini Vaishnaw. The government has also launched AI Kosha, a national dataset platform that aggregates non-personal data from various sources along with an AI Competency Framework to enhance AI literacy among government officials.
This means there is an urgent need for AI related skilling and training enterprise wide. These trainings will need to cover both technical and non-technical aspects, and include staff across the enterprise.
The strategic importance of collaboration between AI and cybersecurity experts must not be overlooked by organizations for safe, secure and effective use of AI in enterprises. Multiple perspectives will be needed to ensure that horizontal and vertical skilling is carried out for AI use in enterprises. Across the board, training will be required enterprise-wide to ensure that staff from those at the front line actually using AI solutions, tools and systems, to those in the C-suite managing risk and related aspects, to those in the board room tasked with governance, are aware of what they are dealing with.
This will entail providing everyone involved with an overview of the different technologies at play, such as machine learning and deep learning, and their applications such as large language models, agentic AI and anything else that is on the horizon. This will enable a better understanding of the AI “beast” that enterprises are dealing with and the operational, risk, governance, audit and other implications of AI use. This will also ensure that users both technical and non-technical are able to grasp challenges such as explainability, transparency, privacy, predictability, interpretability, auditability and others that may be relevant to the specific use case.
Managing risk will require a deep understanding of the technologies involved, calling for a deeper technical skilling and reskilling for not only technical staff but also others involved in the decision making process when it comes to the adoption of AI. Staff will need to understand the inner workings of technologies comprising AI and the risks and points of failure involved. This should also include insights to how data is managed within AI tools and aspects related to the models used and risk, governance, audit and related implications for choices made. Staff will have to be trained on understanding the supply chains involved, the data flows, and most importantly how they will incorporate AI technologies into the enterprise considering evolving regulatory requirements and customer perspectives.
Failure to address skills gaps could lead to double jeopardy, i.e. missing out on the benefits while also exposing the organization to unnecessary risks. Options for AI skilling include courses offering an overview of the fundamentals of AI, like ISACA’s AI Fundamentals course, and from there progressing as per need, including other training on AI governance, ethical perspectives, AI threat landscape, machine learning and even audit of AI.
The way forward will involve the development of a risk-aware governance framework providing everyone in the enterprise the lens to apply to AI use cases and decision making, supported by deep skilling. This should also be supported by organization wide technical and non-technical training to all staff enabling them to use AI solutions effectively and responsibly.
Guest contributor RV Raghu is the Director of Versatilist Consulting India Pvt. Ltd., which is active in India and the Middle East. He is a platinum level member of ISACA, an international professional association focused on IT governance. Any opinions expressed in this article are strictly that of the author.
