Bringing AI into the table in a realistic way is a confusing process. Is AI a complex undertaking that requires profound planning, or is it now embedded in every solution available? 

 Spending on AI is on the rise. ROBO Global research projects that AI and ML spending will top $375 billion by 2025. It appears this is more than throwing money at the least shiny objects. 

According to a senior research analyst at ROBO Global, a majority of the enterprises that they spoke to are not just evaluating AI implementations but are often prepared with ROIs and outcomes they are trying to achieve. 

 The real question is if the risks of not incorporating AI outweigh those of moving ahead with the technology. The picture is mixed when it comes to implementations, talent and digital transformation. 

Complex but easy 

 Many executives expect AI to solve all business problems. Also, they expect AI adoption to be easy. However, this is only partially true. Implementation of a transformative process using AI is a time-consuming process. There are a number of AI companies across the world, and the majority of these companies lack commercial validation and track record.  

 AI might seem deceptively easy, but producing good and meaningful results implies completing many things under the surface. 

 It is one of the AI paradoxes that when business leaders see AI as easier than it is, others see it as more difficult. The novel and bold nature of AI makes some companies intimidated by it. They assume that adopting and deploying such transformative tech must necessarily be a complex and cumbersome process, so they tend to stay away. 

The effective deployment of AI in any enterprise depends more than good programmers and data scientists. It requires domain experts, in this case, someone with deep knowledge on the functioning of the dairy industry and conversion processes.

AI as talent 

"There is a shortage of talent in the workplace globally”, said Libby Duanne Adams, co-founder, Alteryx, in a conversation with INDIAai.

 A number of organizations try to take on projects they don’t have experience in rather than venturing and integrating with a suitable partner that can bring external expertise. 

 One of the most pressing business cases of AI is to augment or fill in talent shortages. AI frees humans from repetitive work and allows them to develop new higher-level skills. It automates mundane tasks and enhances and augments complex tasks. 

 AI can improve the way people work while providing enterprises with better data and allowing them to generate better business outcomes. 

Transforming digitally 

 AI provide immense support to digital transformation initiatives. Efforts to support digital transformation blaze the path to AI as well. In cases with more stern resistance, the adoption happened through digital reinvention. 

 Even the most traditional companies begin to compete effectively in the technological space once digitalization kicks in. Every company is a tech company, and AI is gaining more ground in every old-fashioned industry. Firstly, they drive operations support, and then they involve in driving the reinvention of the business. 

Overcoming paradoxes 

“If you look at any AI solution, there is a domain part of it, and there is a software part of it. We can only find value in the intersection of all these things,” says Nataraju Vusirikala, head of the Bosch Center for AI in India.

Numbers state that 85% of AI projects fail. From these failing projects, it is quite evident that AI is not for everyone. A clear and detailed AI strategy is the foundation of every successful company. However, the ideas survive with the support of skill, technical environment and data.  

The companies should not start from the solution but from the problem. Beginning from a business orientation rather than technical orientation aid in measuring the AI projects from a financial perspective.   

There are a number of AI paradoxes, such as Moravec’s Paradox, that revolve around the ability of AI tools. But AI is more than the share of paradoxes to work with, around and against.  

Mitesh Shah, Co-Founder of Inflection Point Ventures, in the INDIAai webinar, highlighted key values which AI companies can focus on for their business. “The term Artificial Intelligence has recently been a victim of fancy usage. The startup owners should involve the word AI only due to absolute necessity. Entrepreneurs should aim at creating value for their business and idea”. He said.