How To Know If Your Company Is Ready For AI
Currently, there’s a lot of hype around artificial intelligence (AI). Gartner outlines a particularly important research methodology around hype surrounding emerging technologies like AI, which they term “The Hype Cycle.” The social perception around technologies partially guides their development and direction.
But understanding where exactly your company falls on the rollercoaster of hype is difficult. There’s a reason why hindsight is 20/20. Luckily, there ways that you can tell if your company is ready to adapt to a globalizing world that increasingly relies on automation to make work more efficient and scalable.
The Changing Playing Field: Automation, AI, Machine Learning
To prepare for AI, your company needs to start by looking at the industry statistics and what types of tasks its workers perform are able to be automated. Perhaps one of the most famous examples of the advancing coverage of automation manifests through the optimization of computer engines for games like Chess and Go. Google’s DeepMind AI upset triumph over professional Go player Lee Sedol was a dramatic and landmark moment demonstrating just how far technology has progressed with respect to replicating the intuitive decision-making of humans.
The concepts of automation, AI marketing solutions, and machine learning are critical to fully understanding the big shifts that are occurring on an industry-wide scale. Automation usually describes how easily a task that a human normally can perform can be equivalently performed by machines. AI and machine learning go hand-in-hand with automation in that advances in AI and machine learning allow for more complex tasks (and thus more industries) to have their jobs become automated.
Let’s walk through an example and say we’re interested in which industries are going to be most impacted by AI in the near future. A good measure of this might lead you to check out the public data that’s available on the number of jobs per industry (or likelihood) expected to disappear due to automation. Again, there are sources with varying degrees of reliability you can consult.
BusinessInsider, for instance, presents us with a stock list of potential jobs that have the greatest amount of automation in their execution. These lists might help you develop an intuitive sense for the types of jobs that may be automated, but they don’t give the numbers and relationships between work and automation clearly enough.
Meanwhile, McKinsey & Co. give much more detailed reporting based on data from the U.S. Bureau of Labor Statistics among other sources to make the determination that “Last year, we showed that currently demonstrated technologies could automate 45 percent of the activities people are paid to perform and that about 60 percent of all occupations could see 30 percent or more of their constituent activities automated, again with technologies available today.”
Another study by PwC shows that jobs in water, sewage, and waste management; transportation and storage; manufacturing; and retail sales are most at risk for automation. These studies should serve as a strong indicator for whether or not AI is applicable for your industry and by extension if your company can effectively utilize AI.
Assess Your Competitors
Never underestimate the wisdom of social proof. Looking around can help your business gain perspective when addressing the question “How do you know if your company is ready for AI?”
Answering this question requires you to use to same basic approach when you’re considering any other improvement to your company, whether it pertains to optimizing your website or attracting more customers. However, the problem of AI is distinct in its volatility as an emerging technology, which means that looking at what’s going on in your specific industry will be a helpful first step to the yes or no of investing in R&D for AI.
One of the most common ways to do a litmus test for whether or not your company should invest is by taking a look at what your competitors are doing. On an industry-by-industry basis, making an accurate assessment and pouring a bit of money into researching what’s up with your closest market substitutes can help you position your business to be more marketable. The most basic assessments consist of the cookie-cutter SWOT analysis, but your business can also dig deeper by exploring other areas such as:
- Web audits
- Public records
- Secondary research or business databases
You don’t want to be too ahead of the curve and you don’t want to be too behind either. Being at either end of the spectrum when it comes to development presents risks in the form of pioneering costs or the costs of lost productivity and to your business’ competitiveness.
Run a Cost-Benefit Analysis
A cost-benefit analysis should be another one of your business’ go-to tactics for evaluating the feasibility of new trends. For AI, there are a few ways you can start to estimate the impact that automation can have on your business. The first thing you want to do is to tabulate the tasks that you expect can be automated that are currently manually performed by your employees.
Afterwards, you’ll want to note the frequency of the tasks as well as how much value they contribute to your business. Then, perform market research on available automation methods and attempt to quantify the exact degree of substitution an automated method that utilizes AI tech can offer your company.
As an example, assume your company has identified a task that has a number of reliable market methods that allow for its automation. The best automation methods can replicate results by up to 80% according to empirical studies. You weigh the costs of implementation and a 20% decrease in productivity but add the benefits you get from cutting those jobs and the money you save from salaries and you will be able to get a general picture of what AI is worth it.
Therefore, knowing if your company is ready for AI depends on three major things: its grasp of automation, the state of its competition, and a quantitative analysis of the costs and benefits of its implementation.