It’s time to take a quick look into the not-so-distant future. New technologies around cognitive systems and artificial intelligence (AI) are already impacting organizations in a variety of industries. According to IDC, widespread adoption of cognitive systems and AI across a broad range of industries will drive worldwide revenues from nearly $8.0 billion in 2016 to more than $47 billion in 2020.

“Software developers and end user organizations have already begun the process of embedding and deploying cognitive/artificial intelligence into almost every kind of enterprise application or process,” David Schubmehl, research director, Cognitive Systems and Content Analytics at IDC said in a statement. “Recent announcements by several large technology vendors and the booming venture capital market for AI startups illustrate the need for organizations to be planning and undertaking strategies that incorporate these wide-ranging technologies. Identifying, understanding, and acting on the use cases, technologies, and growth opportunities for cognitive/AI systems will be a differentiating factor for most enterprises and the digital disruption caused by these technologies will be significant.”

IDC went on to point out that the industries that will invest the most in cognitive/AI systems are banking and retail, followed by healthcare and discrete manufacturing. Looking ahead, healthcare and discrete manufacturing will deliver the greatest revenue growth over the 2016-2020 forecast period, with CAGRs of 69.3 percent and 61.4 percent, respectively. Education and process manufacturing will also experience significant growth over the forecast period.

Organizations are actively looking at more ways to control their data and create real actionable steps around that data.

AI and cognitive systems help analyze a vast amount of different data types. This means looking at both structured and unstructured data points. Structured data refers to information with a high degree of organization, like text files in easy-to-read formats. Basically, something a data mining engine, with fairly straightforward search engine capabilities, can go through with ease. Unstructured data is, more or less, the opposite. This can be bitmap images/objects, text and other data types that are not part of a database. For example, an email can be considered unstructured data because the data is ‘raw’ and doesn’t really follow a structured (easy for a database to understand) format. From there, correlating and quantifying this information can really impact business decisions.

AI and cognitive systems take this even further. They’ll look at this data, help analyze it, compare it to market trends, and even directly help influence change in the business. Furthermore, they’ll understand how specific processes within the business actually work. For example, order placements, patient entry, student enrollment, and much more.

Here’s the amazing part – AI can actually begin to interact and help you make competitive decisions around this data, and even interact with customers.

“AI is changing the way in which organizations innovate and communicate their processes, products, and services,” Whit Andrews, Gartner vice president, and a distinguished analyst said, “AI continues to drive change in how businesses and governments interact with customers and constituents.”

The Gartner report goes on to state that:

• By 2019, startups will overtake Amazon, Google, IBM and Microsoft in driving the AI economy with disruptive business solutions.
• By 2020, 20 percent of companies will dedicate workers to monitor and guide neural networks.

AI: A Use-Case

There’s a really cool platform from an AI company called IPSoft. Specifically, it’s got an engine called “Amelia” who can basically be considered your very own digital employee. IPSoft acts as a learning engine which learns your business leverages key data points and can understand processes. From there, you can deploy Amelia as a cognitive agent capable of taking on the role of a service desk assistant, customer service associate, and even patient entry assistant.

After learning your business and interacting with data within the organization, Amelia can help with everything from opening a bank account to hospital patient data entry.

Imagine this scenario… a customer calls into an IT business. This is a regular customer who has done business with the IT firm in the past. The customer’s call revolves around a missing component from a recent order. Once the client calls, identifies themselves and references the order – Amelia can talk the customer through ordering the missing part, and she’ll actually place the order as well.

The amazing part is that the entire process works through Amelia as the cognitive agent helping the customer along. No human interaction; just AI working for your business.

Again, this use-case can be applied to manufacturing, healthcare, retail, and much more. Furthermore, Amelia acts as an ever-evolving part of the business. She’ll keep learning and adjusting to the requirements of the customers, the business, and the users.

The key difference between Amelia and other “automated” answering machines is her ability to emulate human intelligence. This helps create more natural interactions between people and machine. She understands human language input, can fulfill customer and user requests, and can actually resolve problems without any human interaction.

Because of this type of learning engine evolving cognitive and AI platforms will be able to automate almost any process within the business.

There are other use-cases out there as well. For example, IBM Watson partnering with H&R Block to tackle taxes. The goal here is to augment the tax professional and find errors as well as further deductions to make the entire tax process easier and more effective.

AI: A Disruptive Technology

Organizations are actively looking at ways they can leverage the vast amount of data their business produces to make better, and more competitive, decisions. Executives should absolutely analyze their business to see what’s underserved, what can be optimized, and where these types of cognitive systems can help. The other great part is that there are partners out there already which can help out. You’ll need to understand your various business segments to actually see where this type of technology can fit in. From there, you can allow your employees to perform higher-value functions within the organization while allowing platforms like Amelia to act as your level-1 support. Remember, the ultimate goal isn’t to replace people – but have them deliver more value to the business. Moving forward, AI and cognitive systems will help augment and improve human decision-making.

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