How Artificial Intelligence is changing the way MNCs work.
To organize employees and manage the work across borders is a crucial task done by multinational companies. As we see, technology is updating every day which leading the companies to adopt such technologies and organize the work culture as much as possible.
Artificial Intelligence is already forcing leadership teams of the companies around the world to reconsider some of their core structure. Advances in technology are causing firms to restructure their organizational makeup, transform their HR departments, develop new training models, and re-evaluate their hiring practices.
In the past two years, Swiggy, the Naspers, DST Global, and Bessemer Ventures-funded restaurant aggregator, has been on a tear. The number of interactions on its platform since October 2017 has gone from 2 billion (across consumers, riders, and restaurants) to 40 billion in January 2019. In that time, Swiggy has gone from a business working with 12,000 restaurants to over 55,000; from seven cities to 70; from the delivery staff of 15,000 to 120,000. The Bengaluru-based venture has become far more valuable, too — from $700 million in February 2018 to $3.3 billion by the end of the year. This dizzying growth has meant that Swiggy, a firm founded as recently as 2014, has to look beyond human intervention to keep pace.
Swiggy is leaning on technology, specifically, artificial intelligence (AI), to help its systems keep pace with this rapid growth. “AI is critical for us to sustain our growth,” says Dale Vaz, who heads engineering and data science at Swiggy. Over the past 12 to 18 months, Swiggy has been expanding this team, putting more resources behind it. The firm has also intensified its focus on building a strong data repository, thanks to the explosive growth of interactions, to catalyze the adoption of AI. A lot of the necessary back-end work in tagging and classification is increasingly done by code that improves itself over time.
The company can today use machine learning to train its systems to distinguish between vegetarian and meat dishes from images, and also to vastly expand the languages, colloquialisms, words, and strings customers could use to obtain accurate results. For instance, the words ‘chicken’, ‘murgi’, ‘murghi’, ‘Koli’, ‘kolzhi’ will all be recognized by the app as a craving for poultry. Swiggy offers users different app interfaces, depending on their individual preferences. The new AI-enabled features will add more meat to its offerings, so to speak. In February 2019, the firm acqui-hired (when you buy a company for the skills of its founders or the team) Kint.io, a developer of image recognition solutions, for an undisclosed amount. “We continue to scout for deals to strengthen our presence in this field,”
For a company like Swiggy, winning a competitive tech advantage with AI is a high-stakes necessity. It is in a heated duel for market share with arch-rival Zomato but sees Uber Eats, Food Panda, and even Dunzo as looming rivals.
In India, Swiggy is hardly the first TechStars to bite the AI apple. Previously, Google, Walmart Labs, Flipkart, Paytm, Oyo, and several other global and homegrown players have all invested in and acquired companies to boost their presence in AI. For much of the past few years, startups and large companies have been running relatively small experiments with AI. Now the momentum in the space is accelerating, as evidenced by a flurry of deals as well as by in-house budgets at unicorns being diverted in this direction.
Like all technology hype cycles, there’s a lot of posturing. AI votaries are pushing CEOs to invest in it, but the challenge is to make sure these investments generate good returns and not get lost in bureaucracy, especially when integrating an acqui-hired company. “AI is past this hype circle,” says Sasha Mirchandani, founder of Kae Capital, an early-stage investor in tech startups. “Now larger contracts are being offered and old economy giants are committing themselves to this emerging field.”
AI refers to the ability of a computer or system to interpret external data and take decisions based on this information. As a field of study, it has been around since the mid-1950s, but technological advancements over the past decade have seen it leap rapidly from the lab to mainstream applications. Several factors have pushed the growth of AI globally, including the availability of massive data sets, the leaps in processing capability with the emergence of GPUs (graphics processing unit), improvement in cloud technology, and the growing sophistication of machine learning and self-improving algorithms.
AI has, of course, been in use among consumers for a few years. For example, on mobile phones, digital personal assistants such as Siri, Google Now, and Cortana all try to learn from the usage and behavior of the phone’s owners. Games such as Far Cry and Call of Duty lean on these technologies. In the world of business, retailers such as Target and Amazon have used AI to predict consumer behavior, as have banks, media ventures, and music streaming services.
AI has become something of a magic wand to wave at all tech problems, even as there’s widespread debate around its utility and optimal applications. Startups focusing on niche areas in AI are receiving investor backing, ventures with strong AI capabilities are now beginning to win deals and customers beyond early pilots and, most notably, specialists in the field, especially data scientists, are in high demand. “At least 25–30% of the proposals we now get involve a significant element of AI,” says Girish Shivani, executive director at YourNest, an early-stage venture capital firm with interest in so-called deep-tech startups. Kris Laxmikanth, CEO of Bengaluru-based HR firm Headhunters, says that the market for talent with AI-linked skills is becoming overheated. Salary jumps of 100–150%are becoming the norm to lure away an established data scientist. There are also instances of Indian AI startups relocating to Silicon Valley in the US for want of relevant talent here.
“AI is a hot skill today. I will even call it super hot. It is hotter than what SAP was in its heyday. In Silicon Valley, an AI engineer can get between $135,000 and $160,000. This is the highest paying skill today. In India, a fresh engineer with AI skills starts at Rs 8 lakh per annum in top software services companies such as TCS and Wipro NSE 1.08 %. After one year, they can command a 50–80% increase if they have the exposure to the right projects like chatbot building. At global tech companies such as Google, these salaries are higher,” says Laxmikanth.
Structural Support
There’s evidence of broader support for AI from big tech and, as announced in the Union budget, from the government. Tech behemoth Google acquired Halli Labs, then a four-month-old startup, in July 2017. However, beyond Halli’s expertise in machine learning and natural language processing (the ability of a computer to understand language as spoken by humans), Google is making deeper inroads into the Indian market.
“… for entrepreneurs, we are working on an accelerator program, based in India, focused primarily on AI/ML technologies. Our global accelerator program has already supported over 30 Indian startups of which six are focused on applied AI/ML innovation,” Google India noted in a blog post in March 2018. The interim finance minister, Piyush Goyal, announced the establishment of a national AI program, in the budget. A national center for AI is envisaged and a portal is expected to be established, too.
According to an estimate in a study by tech giant Accenture, AI has the potential to add $957 billion, or 15% of current gross value added, to India’s economy by 2035.
India ranked third among G20 countries in 2016, measured by the number of AI-focused startups, which have increased since 2011 at a compound annual growth rate of 86%, higher than the global average.
However, some limitations in the Indian market could yet slow the momentum. For one, the quality of data in India continues to be an issue. The diversity of demographics, languages, and use cases limit the ability of consumer applications to learn on the go. Second, despite some changes, India’s startups focused on AI continue to be under-invested by risk capital providers, compared with their rivals in China and the US.
Then & Now: How Some AI Startups Have Fared
niki.ai
FOCUS: Chatbot that helps users discover services and products
FOUNDED IN: March 2015
BACK IN 2016: Helped with bill payments, cab bookings, recharge, home services, and food ordering
NOW: Early pilots have led to customers such as HUL and HDFC Bank
SigTuple
FOCUS: AI-based medical technology solutions provider
FOUNDED IN: July 2015
BACK IN 2016: Short, an automated solution for a complete blood count test completed a comprehensive clinical validation study at a reputed diagnostic laboratory in Bengaluru.
NOW: Business has boomed, with the company’s technology being used overseas too. It is in the market to raise at least $50 million in fresh funding.
arya.ai
FOCUS: Building developer tools to help enterprises build their own complex AI-based systems
FOUNDED IN: October 2013
BACK IN 2016: Working with large companies in the technology and financial services sectors to build these products
NOW: Customer traction is growing with the likes of ICICI Lombard using its tools to hasten insurance claim processing
Snapshopr/ Artifacia
FOCUS: AI-based marketing solutions
FOUNDED IN: June 2015
BACK IN 2016: Was focused on image-recognition technology
NOW: Has pivoted, rebranded, and focused its technology to help companies monetize their user-generated content
