Artificial intelligence grew by leaps and bounds over the years, leaving its footprint across different sectors, including marketing, healthcare, telecommunication, human resource, government, banking and what have you.
The big companies are always on the lookout for new ways to upgrade their workflows. To that end, companies like Apple, Microsoft, Google and Facebook have embraced AI with open arms. Unlimited resources, budget, and market position allow big companies to drive innovations at warp speed. In contrast, small companies find AI beyond their paygrade.
But recently, many small companies and startups have come up with inventive and cost-effective ways to incorporate AI into their business pipelines. Many utilise AI to provide a better customer experience and increase overall productivity and efficiency. According to Fortune Business Insights, the artificial intelligence market was valued at $27.23 billion in 2019 and is expected to reach $266.92 billion by 2027.
AI and machine learning can be incorporated into small and medium companies’ workflows to up their game. Data lies at the heart of leveraging artificial intelligence and machine learning.
Where to start?
Small and medium-sized companies cannot adopt the business model of huge companies for obvious reasons. The big players have the war chest to invest millions of dollars in research and hire the best minds in the business. Such companies also attract high potential PhD holders from top universities to bring in a lease of fresh ideas to the mix. The big firms have the infrastructure and resources to scale at will. Big corporations also acquire small to medium-sized companies to reinforce their artilleries. Google’s acquisition of London based AI startup DeepMind for $500 million, is a good case in point. Even though small companies can’t expand through acquisition, they can accelerate their growth through partnerships and collaboration. Take, for example, Boost.ai, developers of AI conversational platforms. The firm entered into a partnership with Nordic Capital, a leading private equity firm, to expand its footprint. Smaller companies can also shoot for government and military funding for AI research and development.
That said, in a lot of ways, artificial intelligence can be a great leveller what with the proliferation of open-source resources, new cutting-edge AI techniques (reinforcement learning, few-shot learning), and cheap compute power.
According to a Vistage survey, of 1,467 small and medium businesses , 13.6 % are currently utilising AI in their businesses, with 6.9 % utilising it business operations and 6.1% for customer engagement. Almost a third (29.5 percent) of the respondents believe AI is one of the most effective technologies for business.
AI has also made it possible for small businesses to collect a significant amount of data. From sentiment analysis to machine learning algorithms tracking customer preferences and habits (companies like Facebook allow companies of all sizes to use chatbots, which depend on machine learning), powerful data gathering mechanisms are now available to businesses large and small.
Though small businesses have the option to incorporate AI into their workflow, it’s not as easy to compete and develop AI on the same scale as big companies. That said, big companies don’t have it easy either. For instance, take Uber’s case. Uber AI, despite some major breakthroughs over the years, had to wind down its labs. Uber AI’s significant contributions include the introduction of loss change allocation (LCA), Plato, Pyro, Fiber, POET etc. Uber AI couldn’t focus on expansion and new ventures amid the pandemic and ended up laying off 3,000 employees.
Even if AI becomes more accessible for small to medium companies, it’s not guaranteed that everyone will succeed.
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Ritika Sagar is currently pursuing PDG in Journalism from St. Xavier's, Mumbai. She is a journalist in the making who spends her time playing video games and analyzing the developments in the tech world.