Next wave of AI ripples through digital

Artificial Intelligence (AI) is poised to unleash the next wave of digital disruption, and companies must get prepared now. We already see real-life benefits from early adoption and building the capabilities, making it more urgent than ever for others to accelerate their digital transformations using AI. Pursuit of AI-based solutions cannot happen in a vacuum, when digital transformation is in full swing across most of the businesses. Introducing AI-based solutions will have significant implications on how customer experience can and must be enhanced, how data will be used as advantage, how innovative processes will be used in the value-chain and business models will be innovated. We need to be very clear that AI will not completely take over tasks from humans, but will augment their existing activities. Undoubtedly, AI based solutions have the high potential to drive top-line growth for businesses into the future.

Is your business ready for AI?

Finally, evidence of AI starting to deliver real-life business benefit is growing. As a result, investments in AI are growing too and are increasingly coming from organizations outside the tech space. AI has been through a long history of booms and busts, extravagant promises and frustrating disappointments for businesses. As is typical with all emerging technologies, their potential is propped up with a lot of hype in the beginning. It has not been any different for AI. Obviously, mainstream businesses are being cautious about dipping their feet into the water until they can see real value. But, this time around, the potential claimed for AI is different, due to several reasons. Computer power has grown and continues to grow significantly, algorithms are becoming more sophisticated, and connectivity has multiplied exponentially. Perhaps the most catalytic reason for AI’s success this time is the generation & access of data propelled by technologies such internet of things (IoT) and big data from other hand-held and wearable devices with exponential growth of digital solutions. Digital engagement is spewing out a lot more data that is overwhelming the businesses. AI can help significantly in this arena. But capturing the relevant unstructured big-data, cleansing it and feeding it to AI or machine-learning or deep learning modules has continued to remain a challenge.

Expectations from AI are high. The potential is high. Enthusiasm among early adopters, led by technology giants who have made huge investments, is high. But mainstream businesses have been cautious and slow to readily adopt and jump on the band-wagon. Leading sectors adopting AI are high-tech, telecom, financial services, transportation, logistics, automotive, energy, media and entertainment. Right at the heels of these are healthcare, retail, consumer packaged goods, professional services & education sectors. Businesses across all sectors need to consciously decide how they will leverage AI to achieve the expected levels of automation and free up capacity for value-adding growth.

While AI has the potential to fundamentally reshape your businesses and even industries, significant uncertainty remains about how the technology will develop with time. Unfortunately, to many this might suggest a “wait and see” approach. However, there is a need for urgent but clearheaded action to respond to the opportunities and risks that are already apparent. For many firms, this will mean accelerating their digital journey to ensure that they can effectively deploy AI tools. Most organizations foresee sizable effects on IT, operations and manufacturing, supply chain management, and customer-facing activities. AI becomes impactful when it has access to large amounts of high-quality data and is integrated into automated work processes. AI is not a shortcut to these digital foundations. Rather, it is a powerful extension of them.

Get a good grasp of AI

Executives need to know the fundamental capabilities of AI and have an intuitive understanding of what is possible. Instead of simply reading accounts in the media of every new wonder, they could start to experiment. Briefly, AI encompasses every aspect of cognitive computing and other modules that enable its interaction with humans. It helps in decision making using case-based reasoning and expert systems. But at the core of AI is its machine learning capabilities using advanced analytics and algorithms. Machine learning includes data mining, reinforcement learning, supervised learning, unsupervised learning and deep learning based on neural networks. Computer visioning and listening comes from speech recognitions, handwriting recognition, optical character recognition, image & video recognition, and facial recognition. Much of the human interaction with AI is enabled by natural language processing that includes natural language understanding, machine translation and sentiment analysis. AI responds back using speech synthesis, natural language generation, robotic process automation and control of other systems through API’s. Fundamentally, it tries to mimic human intelligence using advanced analytics, rules, and algorithms that learns through pattern recognition. AI as a process takes in vast amounts of data as input in various forms to get trained and build domain-specific knowledge-base to deliver its output of actionable insights.

AI-based solutions could help self-disrupt

Adopting an offensive digital strategy is the most important factor in enabling incumbent companies to reverse the curse of digital disruption. An organization with an offensive strategy radically adapts its portfolio of businesses, developing new business models to build a growth path that is more robust than before digitization. So far, the same seems to hold true for AI. Early AI adopters with a very proactive, strictly offensive strategy report a much better profit outlook than those without one. There is no organization that shouldn’t be thinking about leveraging AI, because either you do—in which case you’ll probably surpass the competition—or somebody else will. And by the time the competition has learned to leverage data really effectively, it’s probably going to be too late for you to try to catch up. Your competitors will be on the exponential path, and you’ll still be on that linear path.