Not long ago, when people heard about “Artificial Intelligence (AI)”, most imagined a world overrun by machines and robots. In contrast, mentions of AI today lead to engaging conversations about how it’s helping businesses innovate and transform. What has changed? While AI has been around for over 60 years, it’s only now that the technology – massive amounts of commodity compute and storage- and techniques – like deep learning, machine learning, and natural language processing – AI is contingent upon are becoming more broadly available, and also have matured enough to support a very broad variety of use cases across every industry. In addition, a big impetus has come from the increased availability of data, which is key to AI development. Just as humans learn and get better over time by processing information, AI techniques like machine learning and deep learning need sufficient data to “learn” and produce results that can simulate human decisions.
AI-based engines are already being used to do repetitive and mundane tasks, thus freeing up employees’ time to focus on new opportunities. In addition, AI can give organizations an edge in today’s competitive landscape, where staying customer-centric is a necessity. The technology is uniquely positioned to help businesses capitalize the opportunities these new-age customers bring. For instance, many companies that have been selling products for years, will soon have to rethink their processes and start selling products-on-demand services and to align with this, it will be necessary to reimagine their business processes. For instance, car manufacturers will have to replace reactive maintenance processes with AI-enabled preventive and even proactive maintenance facilitated by virtual agents that are accessible 24×7.
And it’s not just in the area of sales and marketing that AI can have an impact. It can transform product design and testing, by accelerating and automating processes to get products to market quickly. AI can also help financial institutions mitigate issues in navigating the ever-evolving regulatory environment and staying compliant. In particular, the impact of AI, which has the power to fundamentally reimagine processes, will be felt industry-wide and organization-wide.
While there is tremendous emphasis on AI capabilities like deep learning and machine learning, attention should also be paid to smartly incorporate organizational knowledge to enable AI systems to function at higher cognition levels. This requires us to leverage Symbolic AI techniques, an AI technique that has been around for many years, and with its capability to understand and represent knowledge, it can play a significant role in today’s enterprise ecosystem which demands a broader view of AI.
Explainable AI, is also critical as it is no longer sufficient to merely compute a response that directs the next step in the process or provides necessary input for a complex decision; it is also increasingly important that we know why that response was generated, particularly when there is a need for compliance and regulation.
Finally, current AI approaches work well with training data that is labelled – an approach called Supervised Learning. However, enterprises lack sufficient training data that is labelled, and AI techniques need to evolve towards Unsupervised Learning models that do not require labelled data to train the AI models.
As described above, businesses will need a range of AI capabilities to address the variety of use cases – cognitive automation, virtual agents, robotic process automation (RPA), high-performance and scalable machine learning and natural language processing rank among the top desired ones. But one is hard pressed to find one platform that can deliver all these together, or in any flexible combination desired by businesses. This is where I believe Infosys Nia™ can make a significant difference. It is an integrated AI platform that unifies many capabilities (including the ones I have enumerated in this paragraph) to deliver a more powerful and comprehensive solution which can be integrated into any enterprise landscape.
We have also made Infosys Nia agile and open so that it benefits from proven open source technologies. In the past 12 months, our AI platform has gone through rapid releases to ensure that it is relevant, significant, and true to the mission of delivering Purposeful AIÔäó to the enterprises. We believe that we can only do this by incorporating feedback, inputs and insights gathered from close engagements with customers who have embraced this platform.
With AI, we are all on a journey, which will be more effective by staying committed to building open and agile systems. This can help to rapidly bring new capabilities that will enable AI systems to solve increasingly complex enterprise use cases. For now, I believe we are off to a great start with Infosys Nia by delivering purposeful AI to enterprises.