96% of the total wealth gained by the rich this year on Bloomberg’s Billionaires Index can be attributed to their AI stocks. That includes Nvidia’s Jensen Huang, Meta’s Mark Zuckerberg, Charles Liang of Super Micro Computer and Alex Carp of Palantir Technologies.
AI is ubiquitous – a part of all corporate conversations now about keeping pace in a rapidly changing world. The adage that companies will cease to exist if they don’t change faster than the environment they operate in – is possibly an unspoken fear spurring technology adoption. Apart from the pursuit of disruptive competitive advantage. Microsoft’s Satya Nadella calls it the new factor of productivity. The unrelenting proliferation of Generative AI is accelerating this rapid transformation in unprecedented ways, as industry use cases testify.
Healthcare: AI-driven transformation of healthcare has been dramatic. A critical area is analysis -- of data pertaining to cases, patients and clinical trials, sifting through enormous data sets to assess drug efficacy, or images like scans, MRIs and X-rays. This enables early disease detection, personalising medication at an individual level, and predictive health management at population level. AI can simplify administrative workflows like scheduling, medical coding and billing, and leverage speech to text conversion tools for structured clinical documentation. Combined with wearables, it can support real-time patient monitoring for preemptive interventions. And enhance surgical outcomes with robotics, performing difficult procedures more precisely and delicately than humans.
Energy: A grid outage is the last thing a utility company wants. Because the number of aggrieved customers can run into millions, simultaneously. At one level, it’s about deploying AI for the optimisation of power distribution, predicting demand and responding effectively. And about integrating the grid to receive energy from intermittent renewable sources, including solar and wind. At another, it’s about precluding breakdowns through predictive maintenance, making sense of historical performance and current information from sensors, thus keeping maintenance incidents and costs in check. AI also helps cut carbon emissions, make energy storage more efficient with predictive analytics to figure store-and-release times, and energy trading more profitable with timely buying and selling advice. In oil and gas, cases of AI optimising exploration and extraction proliferate, relating to reservoir modelling and drilling precision.
Transportation: AI helps in creating innovative solutions for this critical sector, enhancing convenience, efficiency, safety and sustainability. Ride sharing algorithms match vehicle availability with passenger demand, using predictive analytics. AI enhances public transportation systems by constantly sharpening scheduling, reducing breakdowns through predictive maintenance, providing commuters with real-time information, and having conversational chatbots address queries. Smart traffic systems deploy AI to make sense of real time data obtained from CCTV cameras, GPS devices and sensors, to regulate road traffic and reduce congestion. Similarly, machine learning algorithms decipher various inputs to steer, speed up or stop autonomous vehicles. In logistics, AI models optimise multi-modal routing, inventory management and warehousing. And the entire sector uses AI widely to minimise adverse environmental impact and enhance safety, employing advanced surveillance systems and computer vision to avoid hazards.
Agriculture: AI powered drones and low earth orbiting satellites equipped with sensors can analyse images to facilitate intelligent, pre-emptive decisions about irrigation, fertilisation and pest control. Combined with dynamic weather data, crop management decisions including planting, harvesting, resourcing, crop selection and rotation have become sharper. Drones can also help in precision sowing of seeds. Autonomous farm equipment can independently and tirelessly perform tasks like harvesting and weeding. AI powered plant genomics is gaining traction to create strains that are disease resistant and give higher yields. And AI applications for monitoring livestock location, health and nourishment are finding takers at larger farms. By revolutionising agriculture, AI is helping settle the debate about the viability of farming.
Retail: AI takes personalisation in retail to the next level. Learning algorithms can figure specific customer behaviours and history, providing recommendations that increase the probability of sales success, including cross-sell and up-sell opportunities, often using chatbots and virtual assistants to do so. AR & VR further enhance this by enabling virtual try-ons. Retailers, with the sharper insights now available, can run more effective campaigns, and trigger automatic reordering to optimise inventory levels, precluding overstocking and stockouts. Effective delivery logistics can result in faster order fulfilment and dynamic AI led pricing can maximise profits. AI can also flag suspicious behaviours, analysing transactions in real time to stop frauds.
And more: The spectrum of AI and Gen AI deployment is not just breathtaking, it’s improving dynamically and consistently. Whether it be for optimising food delivery platforms, procurement departments mitigating supplier risks, culling and deciphering critical information from dense insurance documents, easing client interactions in respect of meetings, presentations and deadlines, improving software engineering, or enabling virtual staging in real estate.
A time to reimagine: The threat of disruption across business is equally real, till it becomes the new normal. According to Accenture, 40% of the working hours across industries can be impacted by LLMs (large language models). Illustratively, Linked-in says AI could impact over half of Indian jobs. It's the right time for governments and the private sector at large to reimagine resourcing -- to reorient industry, help the workforce comprehend these cataclysmic changes provoked by AI, provide more avenues for upskilling, figure how to sustain those who get left behind and ensure job creation doesn’t dwindle. There is no choice, if the future has to be about prosperity, not paucity!
(The author is the founder of Thinkstreet and former MD for Digital Transformation at Cisco APJCH)
