Embrace AI To Build Resilient Businesses And A Better World
How has space for AI evolved over the years? Provide insight into the kind of innovations that the sector has embraced over the years.
By way of myths and stories AI is centuries old. Even our ancient scriptures mention flying machines that worked on human commands. But the concept, as we understand it now, first emerged around the 1940s and 1950s with the machines that can learn and think like humans. The concept gained traction in a big way only at the beginning of 2000s.
Today, there is hardly any aspect of life that has not been touched by AI. We have seen how Uber and Airbnb disrupted the hospitality industry. It has increasingly automated manufacturing. Products like Google Home, Siri, Alexa are being used by a 3-year-old to an 80-year-old. There are cars that don't need humans to drive them. The use of AI in agriculture has helped boost production and provided an answer to the spectra of impending food shortages.
AI came in handy to fight the coronavirus pandemic. Not only is it helping detect cases and trace infected people but has also helped in vaccine development with machine learning algorithms and computational analyses playing a pivotal role in the area.
Firms can have supply chain risk assessment tools that offer visibility across the chain and alert businesses to slowdowns or interruptions
With the world seeing rapid technological advancements, how has technology assisted in AI?
AI itself is a constellation of technologies from machine learning, cognitive capabilities to natural language processing. AI has garnered focus from tech companies around the world and is considered the next significant technological shift after evolution in mobile and cloud platforms. There are four key catalysts for the current AI revolution:
• Advancement in Data and Computing Power (cloud and GPU) that made AI accessible to the masses without enormous upfront investment or being a mega-corporation.
• Proliferation of new tools and frameworks that made exploring and operationalizing production-level AI feasible to the masses.
• Cloud Adoption and investments in AI as a service paradigm: In the past two years, AI as a service has taken AI democratization to the next level by enabling easier prototyping, exploration, and building sophisticated and intelligent use-case specific AI's in the product. There are platforms like Azure AI, AWS AI, Google Cloud AI, IBM Cloud AI that provide AI as a service.
• The democratization of AI knowledge primarily powered by simple-to-use toolset and world-class research contents.
The future is now about Human Augmentation and Composite AI with humans and machines living together to make the life easier, smarter and intelligent.
Impact of Covid-19 on supply chain management and what should companies do to overcome this situation.
The pandemic made us realize, perhaps for the first, just how vulnerable our supply chains are. The impact still hasn't petered out as some companies run the risk of going out of business, especially those running on lean inventories to minimize working capital.
The concentration of suppliers in a single geographic area also made access difficult for those in other areas. Firms need to rethink the supply chain model to ensure a repeat of 2020 doesn't happen.
Much has changed in terms of how businesses operate. There has been rise of remote working, use of software as a service and other cloud-based applications has gone up. Just-in-time manufacturing and lean production strategies in supply chains are being thought through.
Firms can have supply chain risk assessment tools that offer visibility across the chain and alert businesses to slowdowns or interruptions. This insight also can help businesses understand their vulnerabilities so they can introduce redundancies such as suppliers and distributors located in different parts of the world. Companies must diversify the supply chains.
B2B data sharing across the chain can also help reduce risks and attain chain resilience.
What strategy should a company adopt in order to position its growth in India?
Today's enterprises don't need to wait for legacy vendors to get there. Though the pace of innovation in AI is faster than I've ever seen and we're just at the beginning. While AI adoption is increasing, most enterprises struggle to realise the full value of their AI projects and move beyond Proof of Concept to production to harness the business value.
There is no silver bullet here as every enterprise is different.
In India, I would say companies need to re-imagine their business for AI and Human co-existence. I would suggest leaders to leverage AI for high value task and decision-making instead of just workforce reduction as AI implementation cost and maturity will still take some time and it will never be able to bring in the emotional intelligence that we need in India to be successful.
According to me to scale effectively with AI, enterprises need to develop a clear AI strategy, a well-defined data strategy and data governance because data is the new oil (or currency) for enterprises.
Today, organizations that are able to deploy analytics solution to answers questions on "What Happened" "What's happening" and identify patterns are more successful then organizations without analytics capabilities.
Align your AI strategy with business strategy. I would say adopt an ethical AI framework into business strategy. The three pillars of AI innovation-private sector, public sector and academia-would need to collaboratively create an enabling environment.
On a concluding note, based on your robust industry experience and knowledge, what message do you want to put across to the readers/investors/Builders/ CXO's/ business partners.
The world is fast evolving, with AI leading the change guiding the way we live, the way we buy and the way we think, act and take decisions. Future of AI promises a new era of disruption and productivity that will enhance human ingenuity in the "New Normal" world.
It's time for re-imaging business models, supply chains, customer journey and engagement and to be optimistic about the potential of AI to address key socio-economic causes and be positive that the government and businesses will undertake necessary developments for meaningful and ethical use of AI solutions.
Let's embrace the AI and use to build a resilient businesses and better world.