The Future of the AI-Based Enterprise

F5 缩略图
Published March 24, 2021

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, and in some cases, completely replace existing industries. Technology continuously and fundamentally changes the way we live and interact with each other.

Compared to 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.

society of mind

"We will show you that you can build a mind from many little parts, each mindless by itself."

Marvin Minski, father of AI

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 been proven 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 shift healthcare from reactive to proactive, improving overall health and potentially saving lives.
  • The transportation industry uses AI to analyze location and congestion to optimize routes that reduce costs and save customers time.

With Minsky's theory in mind, when we look at 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.

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 is to help improve customer experiences, to deliver personalized products and services, and to automate mundane customer services tasks such as call center support.

  • Personalized product recommendations
    “Two in five executives surveyed, 40%, report that their customer personalization efforts have had a direct impact on maximizing sales, basket size and profits in direct-to-consumer channels, such as e-commerce, while another 37% point to increased sales and customer lifetime value through product or content recommendations. More than one-third of respondents have seen increases in their transaction frequency as a result of personalization strategies." (Forbes)
  • Better customer experience
    Consumers are aware of and anticipate benefits from the use of AI to improve their online experiences: 53% say they are "looking forward to artificial intelligence (AI) making interacting with brands a better experience."
  • Automated customer support with chatbot and conversational intelligence
    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.


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, security professionals have additional resources to defend against cyber attackers.

In general, opportunities in 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 in enterprise business operations. This applies to the areas of IT operations, employee operations, sales, and financial operations, etc. 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 asset 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. "Payback was reported at less than 12 months, with an average 20% of full-time equivalent (FTE) capacity provided by robots. RPA continues to meet and exceed expectations across multiple dimensions including: improved compliance (92%), improved quality / accuracy (90%), improved productivity (86%), cost reduction (59%)." (Deloitte

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 find success, AI efforts must span far beyond any individual enterprise; they 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.

In other words, we need to do the right thing when it comes to applying AI and embrace a culture that is human first.