Founded in 2006 as a traditional software development partner, Desai acknowledged that despite such progression, the company went through a period of adjustment when learning the difference between how the technology is deployed compared to traditional software.
“Traditional software is heavily reliant on business processes, and about following some standard methodologies to implement a standard or define a new process,” Desai explained.
“[With cognitive computing] the focus is on human interaction, and not the interaction with the system as much but the interaction with the data.”
Ultimately, Desai said value can be derived from making machines do what typically, only humans can do.
“In order to do that, the traditional software approach where you just follow business processes doesn’t work,” he said.
“The key distinction is that these machines continue to learn and provide expert assistance and that is only possible if you keep that engagement going.”
According to Desai - who specialises in business analytics, ERP, enterprise mobility and legacy modernisation practices - the process of training a machine is more “labour intensive” on the part of the provider, but also for the customer which leads to longer deployment schedules.
“It always depends on specific use cases and scenarios but typically the learning can take from one month to sometimes six months,” he said.
Yet Desai stressed that such a process was necessary to ensure the system was more accurate, useful and beneficial to the end-user.
“On subsequent visits, the labour intensity goes down but it is up to the client to ensure the system works for them,” he added.
“They are the subject matter experts; they understand what they should expect. Once they deploy it, they continue to train the system to make it better and better every time.”
To maximise emerging technologies, such as cognitive and AI, Desai pointed to the importance of strong partner and vendor relationships, with the sheer complexity of the platform dictating that collaboration should be both constant and concentrated.
But while IBM Watson is Carrington’s flagship offering from an expertise perspective, in such a hyper-competitive market, Desai acknowledged the need to avoid being a one-trick pony in the channel.
“We’ve looked at other products from Microsoft and Google for AI capabilities and although they are not part of our core strategy, we are using them as we see fit,” he acknowledged.
From an AI perspective - a technology once regarded as a large-scale enterprise play only - Carrington continues to engage with a range of businesses, including start-ups, to develop new solutions to bring to market.
“We’re working with a research organisation which has lots of research information and documents which they want to make accessible to some of their consumers,” Desai said.
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