Automation. To many business or government agency leaders, the concept might signify the future — and difficult-to-implement, costly technologies. To rank-and-file employees, a fleeting mention of the word might prompt a wave of anxiety.
But the machine learning revolution — well underway in some industries, on the cusp in others, and holding great potential in nearly every sector of the U.S. economy — is something to embrace, not fear. Entities that grasp this and implement, where appropriate, human-centric processes backed by artificial intelligence will be aligned for success by being more efficient and secure and will create new opportunities for their workforce.
The rise of big data creates challenges in all industries. As the world becomes increasingly reliant on technology, companies and their IT staff are expected to manage an exponential growth of data — and AI solutions will be the best way to deal with those problems and clear obstacles that have long existed.
In many cases, data itself will be key to driving these solutions, but not all data is created the same. In fact, 70% of data science is cleaning data, such as discovering the source of bad data (a misplaced value in a dataset, perhaps). Bad data will only guarantee bad results, dragging down processes built on an algorithm.
Clean datasets, however, open the door to efficiency in processes in unexpected areas. A recruiter, for instance, may be able to sort more quickly through candidates and identify the ideal fit for an organization. Or an organization can analyze market trends, customer behaviors and marketing feedback.
However, even when an algorithm is delivering expected outcomes, it is no time to relax. Ask yourself: do you know why it’s working? If you don’t, you won’t be able to explain why when it isn’t. Think of an automated vehicle — it may perform smoothly and safely during a drive, but perhaps it unexpectedly pumped its brakes at one point. Someone must have an answer for that.
This is one of the reasons humans still play a part in an AI-run world. We can still ask “why.”
One can say pattern recognition is a simple form of AI, and if that’s the case, cybersecurity companies and products have been using it for years in spam filtering and virus recognition technologies. Going further, behavior recognition — observing and learning how a virus acts — could be considered an AI program. In a way, any algorithm is a form of AI.
As AI technologies improve, they can bolster IT security in a rapidly changing compliance landscape, providing constant monitoring. But this is also a landscape where hackers are using similar tools to damage industries of all stripes. Even AI systems themselves open new attack vectors for bad actors.
Again, we turn to the human factor. We are often the first and best line of defense in a cybersecurity attack. Recent research tells us 96% of social action cyberattacks come via phishing emails, meaning organizations are only a click away from a damaging data breach. AI, indeed, changed the cybersecurity landscape, mostly for the better, but an algorithm cannot be the only line of defense.
We are a long way from AI-powered platforms and software making value judgements that mimic how our own minds work (if we ever get there at all), so although automation creates fear of job security, as we’ve discussed, there will remain room for humans in businesses that develop AI processes. In fact, automation can lead to workers taking on more fulfilling work.
When an organization takes a broad look at a process to determine the potential role of automation, it can come to several conclusions. For example, the process may be redundant or repetitive and can benefit from automation, the process may be unnecessary and can be discontinued altogether, or the process cannot be completed with automation but can be revamped to improve its efficiency.
In any of these cases, organizations should be thinking ahead of time about what new tasks it can assign to their workforces. Skipping this step is a missed opportunity to provide more value for the organization’s customer base and shareholders.
Ultimately, the growing embrace of automation cannot and should not be stopped. The economic and efficiency benefits won’t be ignored. But the human factor will continue to have a role as this new technological revolution marches on.