What You Should Expect to See from Artificial Intelligence in 2018

Artificial intelligence (AI) is one of the hottest industries. With huge tech firms like IBM trying their hand at AI-optimized customer resolution systems, and Facebook rolling out more algorithmic-based messenger bots for business advertising, it’s clear that AI is here to stay. What’s even more clear is that we’re only at the tip of the iceberg as far as research and application are concerned. 

That is to say: investors can expect to see many new products rolled out over the next few years utilizing AI-based technology. It will affect every industry, and it will affect it soon. 

That, at least, is one of many lessons to take from a recent McKinsey Study into AI. The McKinsey Global Institute Study, entitled Artificial Intelligence, The Next Digital Frontier, is full of insightful data on the state of AI in 2017, and what businesses, investors, and consumers can expect in 2018 and beyond. 

The study was done via interviews with over 3,000 senior executives from companies that use AI on the impact it has on business and society.

Information of note in the study includes:

Early AI Adopters are Predominantly Characterized by Six Traits

1.     Digitally mature

2.     Larger businesses

3.     Incorporate multiple technologies at the same time

4.     Have C-level support for AI

5.     Incorporate AI into core activities

6.     Focused on growth rather than savings

Unlike big data software innovation, AI is predominantly an internal development between huge firms. 

The survey found that VC or PE funding had little impact on research and development (close to 9%). In contrast, the survey found that all the big companies are invested in their own research and patent production. For example, Amazon and Facebook are designing their own robotics and speech recognition software. In the auto industry, Toyota reports they are putting $1 billion into a research project to explore AI for driverless cars. 

Machine Learning is Seeing the Highest Amount of External Investment

The most common form of external investment is in machine learning software. The study found that machine learning saw between $5-7 billion in external investment during 2016, which is many times greater than the $600-900 million put into natural language software. It’s clear that businesses see natural language bots as merely a stepping stone towards something far more impactful. 

High Tech, Communications, and Financial Services Will Show Major Growth

Looking towards 2018 and beyond, McKinsey highlights these three industries as adoptees of AI before 2020. The benefits of technological innovation are self-evident in a financial sector dealing with fraudulent activity on a regular basis. For example, the study projects that the market for AI-optimized systems of fraud detection will balloon to $3 billion by 2020. Investors should expect to see many industries like this expand in size over the coming years.

Bringing It All Together

The McKinsey study highlights what a lot of people already knew: AI continues to have a disruptive impact in many markets. Mid-sized companies will soon follow suite with the biggest firms and be looking to incorporate their own AI software into internal operations. This represents a great opening for start-ups developing AI or machine learning software to harness.   

Are you seeing disruption from AI in your industry? What do you expect to see over the next several years? Please share your thoughts in the comments section below as I learn as much from you as you do from me.

ABOUT THE AUTHOR:

Jim Barnish is founder and CEO of StartUp Solutions, a boutique consulting firm helping entrepreneurs/startups build scalable and fundable (VC-ready) solutions, methodologies and business processes. Jim's 10 years of experience as a strategic change leader in global and integrated operations, sales, and marketing uniquely qualifies him to the lead the firm. Over the course of Jim’s career, he has successfully worked with companies undergoing accelerated business development, process improvement, change management and operational transformation initiatives.