The Future of the AI-Based Enterprise

This article was written by Geng Lin, Executive Vice President and Chief Technology Officer of F5; and edited by Jonathan Finlay.

Imagine an enterprise like a living organism that will naturally adapt based on the environment. Its products and services, will grow, shrink, defend, and heal themselves as needed. This is the future of the AI-based enterprise.

We are living in an unprecedented time. Technology innovations disrupt existing
industry business models, in some cases completely replace existing industries, and
continuously and fundamentally changes the way we live and interact with each
other.

Compared with the industrial revolution and the Internet revolution, the AI revolution is proceeding at an even faster pace. In the coming decades, AI will profoundly impact every aspect of our daily life, from home, to work, to our society.

In his seminal book, The Society of Mind, Marvin Minsky, the father of AI, put forth a
theory that describes how a ‘society’ of tiny components that are themselves mindless can form an intelligent mind. This is a profound insight.

This theory has largely proved to be true, even though the techniques used to connect these vast numbers of little parts needed to be discovered and go through many generations of trial and error until the convergence of neural networks, machine learning, deep learning, and massive data processing and computing revealed the right combination.

Examples of AI abound in every industry today:

• The financial industry is using AI via chatbots to improve the customer
  experience while reducing costs.
• Telecommunications providers rely on AI-based security to protect customers
  and their own networks.
• Healthcare is integrating Electronic Healthcare Records (EHR) with AI to
  become more proactive than reactive, improving overall health and potentially
  saving lives.
• The transportation industry uses AI to analyze location and congestion to
  optimize routes to reduce costs and save customers’ time.

With Minsky’s theory in mind, when we look at the enterprise business’ digital
transformation journey, we notice that it follows the same path in becoming more and
more intelligent. From task automation to digital expansion to AI-assisted business,
every organization is on a path that intersects with AI and its enterprise.

Broadly speaking, we see three major areas for near to mid-term AI opportunities in
the enterprise.

Customer engagement

The first is customer engagement, the focus being to help improve customer
experience, to deliver personalized products and services, and to automate
mundane customer service tasks such as call center support.

According to a recent survey of 200 marketing leaders by Forbes Insights and Arm
Treasure Data found that 40% of executives reported that their customer personalisation efforts have had a direct impact on maximizing sales, basket size
and profits in direct-to-consumer channels, such as e-commerce. Another 37% said
they experienced increased sales and customer lifetime value through product or
content recommendations.

More than one-third of respondents saw increases in their transaction frequency as a result of personalization strategies.  For example, a U.S. bank recently reported that it handles over 1 million calls per month via chatbots. That helps them to save tens of millions of dollars per year. It is estimated that chatbots will be responsible for over $8 billion in annual cost savings in banking alone by 2022.

Overall, consumers are also becoming much more aware of both the existing and
potential benefits AI brings to their online experiences.

Cybersecurity

The next opportunity is cybersecurity. As the volume and complexity of cyberattacks
have increased tremendously, the efforts to identify and contain cyber threats have
reached beyond human scale. Combining AI with cybersecurity, gives security professionals additional resources to defend against cyber attackers.

Opportunities with AI in cybersecurity include the following areas:

• Automating mundane security tasks such as vulnerability management,
  antivirus, identity management, and mail hygiene. Google increased mail
  hygiene by employing AI to block an additional 100 million spam messages
  per day.
• Performing behavior analysis of vast amounts of signals to identify and block
  seemingly legitimate transactions generated by bots.

The offense vs. defense strategies and innovations in cybersecurity form a never-ending game. As security professionals increasingly adopt AI technologies to fight
automated attacks, criminals, too, catch up on AI and will use it to launch more sophisticated attacks.

Business operations

The third area is enterprise business operations. This applies to the areas of IT
operations, employee operations, sales operations, and financial operations, among
others. In this area, automating the business processes to remove intermediate
human actions is the main goal. AIOps and Robotic Process Automation (RPA) are
the major subareas.

The main areas of opportunity for AI in business operations are in:

• IT operations. With digital transformation, every company is now becoming a data company and an application company. As such, managing the portfolio
  of IT assets is a major task that requires automation and AI technologies.
• Robotic process automation. This is for generic process automation. Low
  code environment, process bot, and OCR-based document processing are some of the immediate impact areas. Deloitte’s Global Robotic process automation (RPA) reported that RPA continues to meet and exceed expectations across multiple dimensions including improved compliance (92%), improved quality / accuracy (90%), improved productivity (86%), cost reduction (59%). It also noted that payback was reported at less than 12 months when an average 20% of full-time equivalent (FTE) capacity was provided by robots.

Challenges remain

While AI for the enterprise has great potential, there are a few bumps in the road. In
addition to the relative technical difficulty of implementing and scaling AI,
organizations face business and cultural challenges:

• To identify the right business use cases.
• To provide strong data governance.
• To recruit AI talent and develop skillsets.
• To follow AI ethics and do the right thing.
• Finally, to understand the social impact of AI on the enterprise.

To attain success, AI efforts must span far beyond any individual enterprise and will
require the industry to work together. Despite these challenges, we believe that AI will fundamentally change the enterprise business landscape, across every vertical and sector.

AI, in the future, will be the new electricity for the enterprise, powering a new era of
innovation and creating opportunities for every industry. We need to carefully
consider such opportunities and remember that in the world of technologies,
machines, and algorithms, AI should ultimately enhance our humanity.