Easy But Hard To Implement, Lacking Talent But Easing Talent Shortages

Listen to experts and vendors discuss the current state of artificial intelligence, and they can forgive the confusion about what it takes to bring AI to the table in a practical way. Is it a complex task that requires in-depth planning or what is present in every available solution? At this time? Is it too hard to find talent to create AI or AI to fill the talent gap? Does AI drive digital transformation or does digital transformation drive AI adoption?

There is no doubt that the cost of artificial intelligence continues to rise. For one project, ROBO Global’s research on AI and machine learning will reach $ 375 billion by 2025. It seems more like throwing money at the latest shiny stuff. Lisa Chai, Partner and Senior Analyst at ROBO Global, says: “Most of the enterprises we have talked to are not just evaluating AI performance, but are often organized with the ROIs and results they are trying to achieve. Decided “. “These are good indicators of acceptance and acceleration.”

However, not all AI initiatives are at the forefront and central to a business plan. “In some cases, it can still feel like a stealth method,” said Diego Tartara, chief technology officer at Globant. AI can bring some risks, but “businesses are aware that greater risks do not include AI in the equation.”

But does the risk of not integrating AI outweigh the advances with technology? Images are mixed, especially when it comes to talent application and digital transformation:

The expectation of installation is easy, but also more complicated. Many executives expect “AI will solve all business problems and it will be an easy adoption,” Chai said. “Implementing the transformation process using AI will take time, a team of AI engineers and in-depth industry knowledge to manage the deployment. “Currently, there are more than 10,000 AI companies out there in the United States alone, and most of these companies have very little commercial validation and tracking records.”

In addition, AI is not plugged in to start delivering results immediately. Instead, it must be part of a long journey that has the potential to change business decisions in the coming months and years. “AI seems as easy to deceive as all you have to do is connect a few lines of code or a box in low code or plug it into a platform and you get results,” Tartara says. “Implementing AI is harder than that. “Doing well and creating meaningful results embodies the meaning of doing a lot of work under the surface.”

In stark contrast, while business leaders may see AI as easier than it is, others see it as more difficult than it really is. “AI is a solid new technology and still a new technology – some companies see it as less intimidating,” said Ajay Agrawal, CEO and founder of SirionLabs. “They assume that the adoption and use of such conversion technology must be a complex and complicated process, so they stay away.”

What could facilitate adoption is “the rapidly growing number of AI products offered As SaaS “Agrawal continues. “Businesses can get started quickly without having to worry about lengthy configurations, re-architecture or replacement, lifting and moving – and start getting value in a matter of days.”

There is not enough talent to create AI, but AI may come to the rescue. Along with creating a business case, there is also the matter of finding or training people who will put it all together. “The biggest obstacle to AI adoption today is the lack of AI talent because it is still a market,” Chai said. Tight work for technical workers. “Too many organizations try to take on projects they do not have experience with, such as AI, instead of investing and integrating with suitable partners who can bring in outside experts. Not only as a provider for a number of clearly defined positions, but as a joint venture partner on the operation of their core business. More AI than hiring a few experts There are operating methods and distractions necessary that may not be right for you. There is talent in the house.

At the same time, one of the most important business ventures of AI is to augment or fill a lack of talent. AI is a way to fulfill new roles that will emerge across the enterprise. “AI, like any other modern technology, frees people from repetitive tasks and allows them to develop new advanced skills,” he pointed out. “In addition to automating global affairs, AI-based solutions can strengthen and expand more complex tasks. AI can improve the way people work while giving enterprises better data and allowing them to create better business results.

Digital transformation drives AI. While many use cases have been developed for AI, the single most compelling reason is to support digital transformation initiatives. Instead, efforts to support digital transformation have paved the way for AI. “In the event of a greater resistance, adoption occurs through re-establishment,” Tartara said. Digital systems. “Whether traditional or analog businesses can understand what it looks like, when digitalization comes along, it means they are effectively competing in the technology space. “Technology companies. Gain more land, first as operational support, and then drive business re-establishment.”

The question that arises from all this is whether AI can solve more problems than it creates? The jury is still out, but so far there has been a lot of promise.


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