How Artificial Intelligence is Boosting Productivity

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“Artificial intelligence (AI) is rapidly moving from nice-to-have into must-have territory for organizations. In fact, nearly six in ten AI early adopters think it will be a necessary element to remain competitive within the next few years. Two-thirds say AI is very important to their organization’s strategy and success”, reports Susan Hupfer for IBM. In fact, 62% of early adopters are reporting that their AI initiatives are exceeding their expectations.

What can AI systems do? AI technologies augment human intelligence to help improve decision making by crunching large amounts of data quickly and being able to generate predictions, relations and recommendations.  This helps managers make more informed decisions faster. Here are some examples of how AI is helping companies boost their productivity:

  • Search. For many companies offering an intelligent search option for employees and customers across fragmented systems and data sources is difficult.  AI search platforms have enabled companies to improve search offerings for both structured and unstructured data
  • Customer care. AI systems are working in a number of ways for customer care departments. In some case, AI evaluates natural language questions submitted via text, web chats or instant messaging platforms. In other cases, AI  allows customer care employees to find faster the right answers to customer questions
  • Workflows. Some companies are also using AI systems to compile “organizational wisdom” to cut down on the bottlenecks that can happen when the same subject matter experts are repeatedly sought out for information
  • Operations.  Equipment and operational based businesses are using the predictive powers of AI systems to identify potential risks for downtime and to better plan for equipment maintenance. These businesses can also use these predictive elements to better manage inventory and supply chains to save money

According to IBM, half of early adopters are already reporting workplace productivity and efficiency.  Think about how AI technology could combine with your business  strengths to improve operations, employee performance and ultimately customer satisfaction.

Early Adopters Report Cognitive Benefits

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IBM explains cognitive computing as follows, “cognitive technology augments human expertise to unlock new intelligence from vast quantities of data and to develop deep, predictive insights at scale.”  Cognitive computing is opening up more real-time opportunities  for many businesses across many industries. In fact, analysts expect investment in cognitive technology to grow from $2.5 billion in 2014 to $12.5 billion in 2019. IBM recently surveyed over 600 decision makers who are early adopters and asked about the benefits they are experiencing.

First, who are the early adopters?  Below is a great graphic from IBM outlining where these early adopters fall within their cognitive uses:

The cognitive early adopters

Here are also some of the reasons why they are investing in cognitive:

  • 65% of early adopters view cognitive technology as very important to their organization’s strategy
  • 58% feel that cognitive is essential for digital transformation
  • 58% reported that they feel strongly that cognitive will become a “must have” in just a few short years

62% of cognitive users are already reporting that their projects have exceeded expectations.  For the most part these early adopters are finding success in three categories: customer engagement, productivity and efficiency and business growth. Here is a break down from the survey:

  • 49% report more personalized customer/user experiences
  • 42% said they have been enabled to respond faster to customer/market demands
  • 46% have seen improved decision making and planning
  • 46% report improved security and compliance
  • 41% have used cognitive to expand the company into new markets
  • 45% report a reduction in costs due to productivity and efficiency gains

Business growth - IBM Cognitive Graphic

The road to adoption isn’t always easy. Many of the decision makers surveyed sited data management and an employee skills gap as challenges. Turning to outside expertise has been key to helping them overcome both challenges.

Cognitive computing is helping many early adopters unlock new opportunities. As more practical use cases develop, we can expect more companies to put cognitive technology to work for them.

IBM: AI 101

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A recent article from Tech Crunch by Devin Coldewey highlights an RFI response from IBM regarding artificial intelligence (AI). Mr. Coldewey writes, “The field of artificial intelligence is so huge, and the potential applications so numerous, that it would be folly to try to explain it all in one — no, wait, IBM just did.” Today we will look at some of the highlights from IBM’s response.

First, artificial intelligence vs. augmented intelligence. IBM prefers to speak to augmented intelligence which is the process of creating systems that enhance and scale human expertise rather than systems that attempt to replicate human intelligence.  IBM further describes their approach as cognitive computing or “a comprehensive set of capabilities based on technologies such as machine learning, reasoning and decision technologies; language, speech and vision technologies; human interface technologies; distributed and high-performance computing; and new computing architectures and devices. When purposefully integrated, these capabilities are designed to solve a wide range of practical problems, boost productivity, and foster new discoveries across many industries.”

How is AI currently being used?  IBM provides the follow highlights by industry:

  • Healthcare – AI is advancing precision medicine through its ability to “ingest” patient information and run it against vast stores of medical research
  • Social Services – AI can be used to predict resource needs from specific population groups
  • Education – AI provides new capabilities to design true personalized learning plans
  • Financial Services – AI is being used to ensure financial resources are utilized well. This can come from the advancement of the applicant approval process or through efficient weighing and processing of insurance needs against risk, costs and regulations

In particular for IBM what started as a contestant on Jeopardy, IBM Watson, is now full blown cognitive computing that can be applied to practical problems in a variety of industries.

Next week, we will feature more on the blog from IBM’s AI 101. Be sure to check back. Until then you can also read more on AI and cognitive computing here.