The Future Of AI: The Voice Of The Enterprise

The words “Beam me up, Scotty” created an indelible memory in my mind over thirty years ago. Never before would have anyone imagined that in as many years the world would be ushering in an era of artificial intelligence powered conversational platforms for business.

As a teenager growing up with the sci-fi television series “Star Trek” I was fascinated with Captain Kirk saying the lines “…..to boldly go where no one has gone before.” Such powerful portrayal of the future played a part in inspiring me to go after computer sciences as a specialization in college.

All those years of dreaming, and now the association with analytics and AI, have led to one absolute reality that in the short span of perhaps 18 to 24 months a wide variety of businesses globally will be working with algorithmic powered conversational platforms that serve as intelligent business advisors.

May I be bold enough of saying that the era of Jarvis (from Iron Man), for the sake of a younger audience reading this, is real, and is here to stay. This is the first step in technology evolution before we get to the “beam me up, Scotty” universe.

At the heart of all of this is the data revolution, around both structured and unstructured, as well as enterprise and external, that every organization wants to make sense out of to make intelligent business decisions.

Before I talk about the rise of voice-based business assistants, in analytics, there are two key trends that I notice as a CTO that will fundamentally change how a business leverages data and technology. I feel these are trends which the business CxO must take seriously if they have to prepare their organizations for the future.

The first trend being better understood and getting widespread attention today – machine learning based algorithms applied to all business processes and use cases thanks to the dramatic fall in compute, storage and bandwidth costs on the cloud alongside capacity being elastic and virtually unlimited, but also importantly coupled with advanced machine learning frameworks and capabilities starting to become a commodity.

The second trend, which is unique and still emerging, can be called “natural language consumption” of data by business stakeholders on the back of technologies including but not limited to natural language processing (NLP), voice recognition, intent analysis, machine learning and deep learning.

We are already seeing these deployed at scale in the consumer world with Amazon Alexa, Google Assistant, Apple Siri as well as other Intelligent Personal Assistant’s (IPAs) and the same trend is going to play out in enterprise now. This is akin to the adoption of the smartphone by consumers before it penetrated enterprise use cases.

The rise of the AI-powered personal business advisor to drive decision making

These shifts in computing are going to take greater precedence in business in the coming months and will signal the advent and eventually mass adoption of what is interchangeably called as the AI business assistant, or advisor, or more formally labelled as the Cognitive Expert Advisor (CEA) by leading analysts.

This conversation-based consumption will be powered by technology that understands human spoken natural language that can slice and dice massive amounts of data, and also invoke algorithms, to present intelligent insights and even prescriptions in a very contextual and timely manner to business.

These business advisors will be pre-built and pre-configured for specific industries and verticals, and will be tuned for use by specific roles and individuals. Under the hood, they will activate all kinds of descriptive, predictive and prescriptive analytics leveraging a wide spectrum of technology from rules engines to advanced data science models, and will have learning and feedback built-in.

This is the future of AI and it is nothing but software that can learn, predict, adapt, function and now converse – all autonomously.

There are several AI platforms, tools, frameworks and solutions in the market today that can help put together the capability of such an advisor but it is important to figure out which ones best fit the needs of your business and objectives.

Business, which will be the ultimate customer of the business advisor, should work with solutions that have several references from customers. But it is early days for AI-powered business advisors in the Enterprise so some experimentation is in order. However, a decision-maker such as the business CxO must also know that artificial intelligence without a set of defined objectives is meaningless.

A successful AI based solution needs to be rooted in specific domain, function and data model. That requires a lot of wiring and integration.

With AI, there is no one size fits all. Businesses today have to figure out what they want to do with their data and what objectives can such systems help with. There is a tsunami of change coming and companies have to prepare for a world of contextual and prescriptive use of the data both generated by businesses internally as well as extraneous data from the cloud, social, mobile, IoT first world.

I may be a bit bold in saying that in a decade or less, several leading companies and businesses of today may become redundant if they don’t start to think about and ultimately leverage such systems. But that’s the future, and a reflection of the pace of innovation and disruption underway.

Once a business signs up with a given solution, they can tinker it to customize it to their verticalized use cases that would be most important to solve. Although insights are presented by several analytics tools today, most systems are not yet prescriptive.

Further, conversational systems in the enterprise are still in their infancy and present a very big opportunity to make data and analytics accessible to a very large spectrum of business users and roles without the need to burden them with learning new software.

Large technology corporations such as Amazon, Microsoft, and IBM, who provide AI platforms, can be partnered by services companies that have the deep vertical expertise to put together end to end offerings that serve as business advisors that are role specific to drive more intelligent and automated decision making.

This is a great opportunity for technology and services companies to collaborate with business to move ahead into the future faster.

These business advisors will eventually apply to every type of business role and help them do their job in the most optimal manner. So for example, a CEO will get his or her daily business bulletin over voice first thing in the morning over a cup of coffee without leaving home.

The bulletin will summarize key business updates, company metrics such as sales and margin, the success of new product launches, the performance of key regions, and importantly spot and alert anomalies in the overall performance of the business that need to be looked into urgently.

Further, the business advisor will identify key causal factors for any decline in business performance, and prescribe actions to alleviate key issues. Eventually, the biggest benefit of such systems will lie in their prescriptive capabilities.

Taking another example, each store manager on the retail shop floor will be continually conversing with their business advisor on the go and getting recommendations on how to drive up sales by the hour, what strategies and actions to take based on real-time data including sales, inventory, customer, and other enterprise data but now also marrying extraneous data elements including weather, competition, social sentiment, etc.

Thanks to such innovation the analytics industry is on the verge of disruption. These conversational platforms for business will be highly context-aware, will enable discovery, and also track complex business processes and outcomes based on billions of data points, and in real time if required.

I predict that in 24 months, 25% of all CxOs will start to use such platforms to boost their revenues, improve profitability and drive down cost.

How should the CXOs plan for this?

• Pilot best of breed AI on cloud platforms and solutions
• Experiment with AI capabilities with specific business use cases and objectives in mind
• Start to invest in AI-powered conversational systems applied to a variety of use cases and business users
• Be ready to invest for impact and be patient since there are no out-of-the-box solutions
• Closely collaborate with businesses
• Move as fast as possible to AI-powered prescriptions and actions

Now to paraphrase Star Trek “Analytics and AI is the final frontier. These are the voyages of the Enterprise. Its continuing mission: to explore strange new worlds, to seek out new behaviours and new patterns, to boldly go where no one has gone before