Layoffs in big tech have sent shock waves across the corporate world. If these seemingly recession-proof giants feel the pressure, what chance do small and mid-size companies stand?
Juxtapose this with the news of mammoth investments in AI by the same big-tech companies, and one thing becomes abundantly clear; the AI and ML revolution is already here and will determine who survives in the future and who doesn’t. Microsoft’s $10 billion investment in Open.ai’s ChatGPT is just one example of how the race for ultimate supremacy in the field of AI is heating up.
The past three years have really tested leaders in India beyond reasonable expectations. The 2023 downturn now presents one more challenge, but instead of backing down, there is a visible difference in the approach organisations are taking this time around.
December-January are typically slow months in Australia, where I am based, so I spent the better part of these two months on a whirlwind tour of India. During this time, I met several CIOs, CXOs and AI industry experts across different sectors. One thing completely surprised me. These leaders actually see investments in AI & ML as their top priority and are looking to increase their spending because of the current economic conditions. This is a complete departure from the earlier approach of organisations to hunker down and weather the storm simply.
The old downturn playbook had a standard script: Decide on the % saving one needed to achieve and keep trimming till you got there. Panicked executives facing enormous pressure from investors would impose cuts across the board to achieve this % cost reduction. This brute-force approach guaranteed that cuts would hurt as much as they would help, as they were desperate measures independent of the organisation’s long-term strategy. By pausing long-term strategic projects and letting go of specialised talent, sustaining growth once the market conditions improved, became extremely difficult.
Having learned from previous recessions, leaders helming organisations with a sound business model and a ‘moat’ see investing in AI talent and technology as a catalyst. A catalyst that will help them achieve maximum productivity -minimum waste by creating highly reliable models which can process humongous amounts of data, churning out insights that can predict events with an accuracy that older models and technologies just cannot come close to.
Of course, while all of this is possible, there are challenges which need to be addressed first. For one, large organisations find starting an AI project as a pilot or POC easy, but when it comes to scaling the same AI project, challenges start cropping up. These challenges have both hard and soft aspects. The hard aspect manifests in the form of legacy systems, siloed data, and a lack of technical expertise. The softer aspects are resistance to change, fear of redundancy in the workforce and lack of understanding of the tangible benefits and advantages for the organisation for some key gatekeepers.
Luckily, India has a massive advantage over other countries in the region. India has one of the world’s largest pools of artificial intelligence talent, with over 16% of the AI workforce being based in India, as per a recent report. With the support and emphasis that Govt. of India has placed on AI, evident from this year’s budget, this number is bound to grow exponentially. It’s a matter of time; before the world will come knocking on India’s door for everything AI.
I believe business leaders will have to approach AI adoption differently from the adoption of other technologies due to the perception challenge AI faces. While most leaders understand and acknowledge that AI adoption is a question of when and not if, they will still have to deal with the mistrust and fear that large-scale AI adoption still generates in the workplace. The economic downturn and subsequent layoffs have further accentuated this. That is why leaders must first create an AI vision board for the organisation and then transparently communicate the complexities and values to build trust and, eventually, a Pro-AI culture. Leaders who do this can accelerate AI adoption for their organisations much faster than those who don’t.
Views expressed above are the author’s own.
Views expressed above are the author’s own.
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