How Cognitive Computing and AI Drives Disruptive Innovation

by September 15, 2018 0 comments

Cognitive Computing

An enterprise’s response to existing or emerging products depends upon its approach towards the two terms of machine thinking – artificial intelligence (AI) and cognitive computing. Is your enterprise an early adopter when it comes to leveraging technology to automate enterprise processes, configure chatbots, embed sensors or improve customer experience by drawing insights? Does your company stay on a constant lookout for fresh data sources coming via ever-increasing interactions or does it prefer to observe these changes from the sidelines, not sure of whether to adopt them or not?

Three years ago, the C-suite was engaged in a fierce battle to bring disruptive technologies and innovations to the market. But today on an average, the C-suite is less inclined to view competition from outside the industry as a threat and is focusing extensively on searching for innovation externally among partners. Drawing on inputs from nearly 3,000 C-suite executives, a study conducted by IBM helps answer crucial questions. Is disruption abating? And are companies now more likely to ‘stay in their lanes’?

First, some brief description of the two types of machine thinking. Cognitive computing makes use of artificially intelligent technologies, data and analytics to continually build knowledge, understand natural language and learn to reason and interact more naturally with humans. On the other hand, AI solutions can be understood to have some but not all of the intelligent characteristics of the cognitive systems. Say, for instance, automation now refers to commanding complex systems and interacting and not just moving datasets from one point to another. Therefore, the most fundamental difference between the two is that in case of a cognitive system, it supplements a human being’s decision-making process whereas an AI system is the one that makes the decision by acting upon the best possible algorithm for a given situation.

IBM’s study segmented the respondents on the basis of the extent of AI used by them to automate their business processes as well as their likelihood of investing in this technology over the next two to three years.

Overall, 34 percent of the surveyed organizations planned to push forward with the AI technology. A deeper analysis revealed significant differences in capabilities, strategies and future views of the organizations. These differences led IBM to classify the organizations into four distinct groups – Reinventors, Tacticians, Aspirationals, and Observers.

About 11% of the surveyed CxOs belonged to the Reinventors category. They solve complex problems, infuse intelligent capabilities into their business processes and invest to create a new and a better future by taking a strategic approach to enable their organization with AI technologies. Their aim is to advance innovation as part of an ecosystem by transforming both business and operating models. Reinventors collaborate more extensively with their partners to share resources and assets, thereby continuously reinventing their businesses.

The Tacticians group focuses more on remodeling parts of a business rather than remaking the entire organization. They are updating selected activities with AI point solutions. 28% of the surveyed CxOs fall in this category and this group is generally more insular than the Reinventors and therefore is less likely to look outside the organization for innovation or share resources with partners.

To overhaul their enterprise in the face of industry convergence, cybersecurity risks and shifting consumer demographics, the Aspirationals comprising 23% of the surveyed CxOs, are still plotting and finding their ways into the world of AI. They expect AI to be instrumental in cross-enterprise transformation and a subsequent shift to ecosystems.

Lastly, a significant 38% of the surveyed CxOs are yet to embrace AI. Among the Observers, few have been impacted by the recent disruptions in the field of AI and for the larger part, they still intend to remain on the sidelines and observe changes in other businesses.

The distinct feature which sets the Reinventors apart is that they anticipate what others don’t. They don’t follow traditionally integrated business models, rather believe in an open and expansive ecosystem. In this study, there were twice as many Reinventors as Tacticians and are high performance and innovative organizations. Out of ten, seven Reinventors reported a better revenue growth and profitability than their industry peers and nine in ten said they lead in innovation in their industry.

Reinventors also face twice as many disruptions in their industry as the Tacticians but are confident of having the wherewithal to manage the coming changes. Aspirationals, on the other hand, are less prepared to manage the disruptions. Reinventors and Aspirationals are remarkably alike in the sense that they both are proactive and positive in terms of technology convergence and the belief that AI will not threaten employment and only increase retention and productivity.

AI and cognitive computing will help search out hidden opportunities, individualize customer experience to increase retention & help in operational flexibility to support new capabilities. Traditional operating models will have to undergo commensurate changes to help transform the business model itself and to stay ahead in the curve.

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