Perhaps the greatest promise offered to businesses today stems from cognitive computing technology. These systems can process unstructured information in ways like humans, but much faster. They understand language patterns and sensory inputs, including text, pictures, and audio. The systems are already improving employee and customer experiences, streamlining new product innovation, enabling health care providers to spend more time with patients, and even saving lives by identifying customer safety issues before they cause accidents. Cognitive computing, also known as AI or smart machines, will impact the economy across many industries.
To learn more, check out the infographic below created by the Ohio University online Master of Business Administration program.
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Cognitive computing is capable of processing large data sets exponentially faster and more efficiently than people. Data mined from cognitive computing’s early adapters back up this sentiment. 33% to 66% saw large improvements in areas of customer engagement, productivity, and business growth. 46% had an outcome of improved security and compliance along with reduced risk. 42% noted it delivered faster responses to customer and market needs, while 39% of early adapters experienced outcomes of accelerated innovation of new products and services.
A big reason for this efficiency boost is because cognitive computing allows users to work with larger quantities of data that weren’t useable before. 80% of all available data are unstructured, a category that includes text files, videos, websites, and mobile data. This data was unusable prior to cognitive computing’s advent.
As cognitive computing’s potential begins to be realized, concerns develop. These include the need to implement safety-ensuring monitoring systems, developing legal policies for usage, creating early warning systems for potential system fails, and the costs and time involving cognitive systems training.
Cognitive computing can improve product safety in the automotive industry. In 2016, a record 53.2 million vehicles were recalled around the globe. The safety issues behind these recalls have a serious impact on businesses, as they can create harm to customer, generate negative publicity, incur regulatory penalties, and cause expensive lawsuits. Cognitive computing improves safety by quickly analyzing usage data like crash reports, identifying emerging issues before escalation, recognizing malfunctions, and determining the best course of action. 70% of auto industry executives believe the tech will have a substantial impact on vehicle safety – and impact that can ultimately save lives.
Healthcare can use cognitive computing to quickly parse immense quantities of data to target patient medical issues. This is crucial, because the volumes of patient-related data are exceeding human cognitive capacity and proving impossible to completely integrate without the use of new AI models.
For instance, it’s projected that by 2020, 2,314 exabytes of health care data culled from items like electronic health records, genomic data, and practitioner’s notes will be processed. To put this in perspective, 1 exabyte equals 1,073,741,824 gigabytes. Furthermore, the medical data footprints will double every 73 days. As such, it would take a doctor 150 hours per week to review every piece of data published in their field of interest.
Cognitive computing helps time-strapped physicians make decisions quickly. One case study indicated that nurses were able to shorten the time spent aggregating information after implementing a cognitive computing solution. Other cognitive computing studies point to early success stories, such as accelerated innovation of new products and services and improved customer engagement.
Reinventing Human Resources
Cognitive computing could improve HR decision making. Studies show one in five hires are “bad hires” or are “regretted decisions,” which could cost businesses time and money. 65% of CEOs surveyed believe cognitive computing will provide substantial value in HR functions, including more efficient hiring. 50% of HR execs surveyed also believe that cognitive computing possesses the power to transform core HR dimensions. Ultimately, predictive analytics streamline pre-hire assessment, improve the candidate’s experience, and remove bias in the selection process.
This also has an impact on the employee experience. Natural language processing and game mechanics are being successfully used for ongoing employee performance reviews, with one case study showing an 11.4% increase in employee productivity. Employee listening programs are also being used, and these can help leaders identify innovation, halt discord, and boost productivity while also giving employees a voice, ultimately building a link to the company and its mission. Cognitive computing can also improve new hire support, personalize workforce development, and better support employee benefit usage.
Cognitive computing, along with data analytics, enable marketers to tailor content to their customers. Marketers utilize the tech to manage and collate a host of relevant data from various metrics, including predictive analytics, website performance, audience research, and social listening.
The tech appears to be the foundation of the next great technology shift, transforming the job market and impacting many parts of the economy. The financials reflect this sentiment. Big data related hardware, software, and professional services are expected to be worth $61.16 billion by 2020. The “smart machine” market will have a projected value of $41.22 billion by 2024, and the market for predictive-analytics software will be a projected $6.5 worldwide by 2019 – a number representing a annual growth rate of 17.8% since 2012.