Adoption of Cognitive Computing Across Various Industries
One of the most comprehensive amalgamations witnessed in recent times – cognitive computing, is a unique blend of artificial intelligence, natural language.
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Key takeaways
- One of the most comprehensive amalgamations witnessed in recent times – cognitive computing, is a unique blend of artificial intelligence, natural language processing, machine learning, neural networks and other scientific disciplines.
- These systems are designed to parse through data, share health information, improve patient outcomes, and personalize patient care by helping medical professionals make faster, cost-effective decisions.
- In summary, cognitive computing bears true potential to transform the way technologies such as artificial intelligence and natural language processing are deployed.
One of the most comprehensive amalgamations witnessed in recent times – cognitive computing, is a unique blend of artificial intelligence, natural language processing, machine learning, neural networks and other scientific disciplines. Essentially cognitive computing is an advanced framework that combines the aforementioned and uses computerized models to imitate the human thought process. Note however, that it is very different from proper AI-enabled systems – cognitive computing studies patterns and analyzes factors to help humans take a relevant course of action.
Given its incredible ability to think and process like humans, cognitive computing is heavily used in decision-making across major verticals. To that end, even prominent companies have been working to invest in cognitive computing solutions – consider Kanverse.ai for example. The firm, recently in May 2021, announced that it is launching the Datolite release of its AI-powered IDP (Intelligent Document Processing) Product for Enterprise. This IDP is built on the Kanverse Cognitive Automation platform that integrates artificial intelligence with Business rule framework, Optical Character Recognition (OCR), and Automation to deliver a product for digitizing the entire document processing for enterprises.
Ultimately, the aim of cognitive computing is to stimulate human thinking within computerized models. Over the years, it has been deployed across many verticals, with path-breaking results. IBM’s Watson for instance, has been used in the medical realm, to collect information about specific disorders, including but not limited to basic details, patient history, journal articles, diagnostic tools, treatments, etc., analyze the same, and eventually provide a recommendation. This literally changes the course of how humans perceive AI-enabled tools – through cognitive computing, interacting with tools could become a much more seamless process.
The following paragraphs provide a gist of the use of cognitive computing across major industry domains:
How cognitive computing is revolutionizing the banking sector #
The BFSI industry has been prompt in adopting technologies that make financial processing easier and less complicated. The realm of banking comes with its own set of processes – fund transfers, cash deposits and withdrawals, bank statement accountability, and most importantly, resolving customer queries. Although most financial institutions have been quick to deploy virtual assistants and bots for the customers convenience, it has become obvious that people would prefer interacting with something with a slightly more human touch. Here’s where cognitive computing steps in to ensure seamless consumer experience.
Banks and other financial establishments are leveraging cognitive computing to automate banking and investment products, manage a large amount of transactions, and use evidence-based information to provide tailored services to customers. Using cognitive computing helps banks examine and analyze data from a wider array of resources so they are able to mitigate risks better. Banks can also use CC for fraud detection – to predict what may happen, even before an activity actually occurs.
The predictability factor of CC is particularly useful in trading. As a matter of fact, data and analytic provider Previn states that close to 1,360 hedge funds leverage computer models to make the majority of their trades. Many a time, high frequency trading is completely automated, in which case business models can analyze large amounts of data and use the same to improve trading outcomes, all by themselves.
Wipro’s recent partnership with Finastra to accelerate digital transformation across APAC corporate banks is an example of the BFSI sector has been incorporating cognitive computing in its processes.
Cognitive computing is on its way to transforming the healthcare sector #
The incorporation of technologies, such as Big Data, AI, imaging, has brought about a tremendous change in the medical sector. Healthcare companies have lately been leveraging cognitive computing to make vital decisions regarding a patients condition, diagnosis, and treatment. CC is also being used by companies to as a clinical support tool – in the future, it is likely to be used in monitoring systems that scrutinize episodes in patients suffering from asthma, Parkinson’s disease, diabetes, and more, without human intervention.
As the complexity of diseases and the number of patients in the medical ecosystem increase, healthcare personnel often find themselves in trouble as they have to deal with a vast amount of health-related data in less time. Not to mention, this data is pretty fragmented and does not provide a concise insight into a patients medical history and decisions to be taken for the patients overall well-being. To that respect, cognitive computing systems step up as an efficient solution. These systems are designed to parse through data, share health information, improve patient outcomes, and personalize patient care by helping medical professionals make faster, cost-effective decisions.
IBM’s Watson is one of the best examples where cognitive computing is being used to process data and model possible solutions. IBM has worked with a lot of hospitals in partnership, especially Cleveland Clinic that has been using IBM’s Watson cognitive computing technologies across its clinical and administrative operations.
Cognitive computing – Bringing about a change in the education domain #
Cognitive computing can prove to be a game-changer in the field of education. With the arrival of the pandemic, the education sector has undergone a massive change. Online schooling became more commonplace, pushing the education technology industry trends to a considerable extent. Amid this scenario, the rise of cognitive assistants will prove to be highly helpful for teachers, students, and other support staff.
Cognitive computing systems can act as a personal tutor for students, as they guide them through their coursework and help them make decisions about which course to opt for next. They can also personalize course materials for students, help them resolve problematic situations in the course, and play the role of career counselors – a job that is crucial in educational institutions.
Cognitive computing solutions are also incredibly useful for teachers. An analysis of the education system worldwide often points to the problem of teachers not being able to answer queries satisfyingly, from students owing to their varying abilities and learning aptitudes. To that end, cognitive computing systems can help teaching staff, as they have the ability to digest large data sets and engage with humans in natural language. For instance, if a student asks a specific doubt to a teacher, he/she can feed it into the cognitive system, which will not only provide the right answer but also explain the steps en route.
The efforts put into implementing cognitive computing in education are quite visible off late. For instance, recently, in August 2021, the department of science and technology (DST) announced a funding of USD 134,848 to establish a cognitive computing hub at IIIT (Indraprastha Institute of Information Technology Delhi), Delhi.
An overview of how cognitive computing is deployed in the retail industry #
Personalized customer experience has been, since long, a cherished dream for retailers. While the e-commerce sector has been quick to adopt novel technologies to ensure a seamless consumer experience, introducing cognitive computing systems into the mix may change the game altogether.
These solutions can be used to create personalized promotions, recommend products during online shopping, generate in-depth customer insights, check on workforce utilization and optimization, and optimize inventory. As online shopping continues to gain precedence, retailers will need to incorporate more and more cognitive computing solutions in their processes to offer personalized, seamless user experiences. These solutions will help retailers track patterns in customer data, derive customer insights, and lead to improved customer interactions.
Apart from that, cognitive computing provides the advantages of predictive analytic, voice assistance, demand forecasting, social media engagement, price optimization, and personalized recommendations. It is also incredibly beneficial for consumers, as it provides then with self-help applications such as self-checkout payment platforms, price checkers, information kiosks, and mobile payment apes to improve their online shopping experiences.
The Future of Cognitive Computing #
There’s no doubt about this, cognitive computing is here to stay. Most experts are certain that it’ll lead to exciting growth opportunities across major use-cases. It has the ability to revolutionize key industry domains, as they scramble to resolve their current challenges. Advancements in cognitive computing will encourage companies to be more receptive to the technology and increase its adoption. In summary, cognitive computing bears true potential to transform the way technologies such as artificial intelligence and natural language processing are deployed.
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