Artificial intelligence can be many things and some of those will affect your bottom line.
One reason the term artificial intelligence (AI) causes so much disagreement and fear is that it is such a broad term. AI can include everything from spreadsheet formulas that automate difficult math to Brent Spiner’s nearly human android in Star Trek – and a host of real and imagined scenarios between those two.
Are we looking at a terrifying future where AIs become sentient and end humanity? Will our jobs be taken by faster, better, smarter blocks of inscrutable code? That’s fun to speculate about. It’s also thrilling to live in times where this is a real question rather than a science fiction plot point.
The truth is, though, that the term AI describes a vast array of tools. There is little doubt that recent AI developments are poised to bring massive change to the way we live and work. But there are task-specific AIs that are already helping smart companies realize greater profits.
What kind of AI is this?
According to McKinsey, AI is “a machine’s ability to perform the cognitive functions we usually associate with human minds.” Or, as IBM explains, it “leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.”
Given how various the tasks performed by the human mind are, this can mean nearly anything.
“It is a catchall term,” according to Oracle, “for applications that perform complex tasks that once required human input, such as communicating with customers online or playing chess.” The term AI, continues the Oracle explanation, “is often used interchangeably with its subfields, which include machine learning (ML) and deep learning.”
This is an important distinction – and the point where humans begin to get anxious. We don’t mind getting assistance from a machine for tasks that are time-consuming and difficult, but we aren’t ready to be replaced – or ruled – by AI capable of independent thought or even to welcome an android coworker like Data into the office.
“Artificial intelligence,” according to SAS, “makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.” This explanation hints at our fear of sentient and autonomous machines. But, according to SAS, “most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing. Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.”
We live in wild times. But we aren’t facing our robot overlords quite yet. What we have now are intelligent assistants. We have trained them. They aren’t here to take over – yet.
As you contemplate the possibility of harnessing some of this artificial intelligence to lighten your own workload, you might ask, “Can I trust it?” or “What type of AI is this?” or even, “Is the data it’s using trustworthy?”
These are heady questions. And the answers are complex and in a constant state of change. But they are not, perhaps, the most compelling questions to ask.
What can AI do for me?
If you are thinking about AI in practical terms – how should I be using it? – the first question you should probably ask is, “What can it do for me?”
Framed that way, the answers are compelling.
While generative AIs such as ChatGPT are getting much of the limelight, there are numerous task-specific, hard-working AIs quietly showing up to work, helping businesses realize greater efficiency and improved – faster –profits.
42% of the companies that are leading the way in AI adoption have already seen a return on their investment that exceeds expectations.
– Accenture
According to Accenture, 42% of the companies that are leading the way in AI adoption have already seen a return on their investment that exceeds expectations. These businesses are largely using targeted, specific tools – sometimes called “narrow AI” – to do work that is burdensome or impossible for humans but that improves processes, delivers better service, or helps humans work smarter.
Some examples from the Accenture report include:
A food delivery service that uses deep learning to guide drivers to the best delivery routes. This AI analyzes over 2,000 variables to make route recommendations in real time.
A large chemical and energy firm uses a combination of drones and AI-powered computer vision to monitor equipment in remote locations.
One of the world’s oldest urban rail systems used AI to analyze vast stores of data – air temperature, train frequency, and customer patterns – to reduce its energy intake by 25%.
Another AI, according to Deskera, is used by digital businesses to enhance revenue recognition. Since calculating revenues for subscription-based digital business is complex – with usage-based pricing, bundled tools, multi-element products, and freemium offerings – these businesses are using AI’s aptitude for analyzing large data volumes to scrutinize contract terms and pricing structures to calculate subscription timing and fees.
Moovila’s Perfect Project is a task-specific AI that helps humans manage projects that are too complex for humans to do well. It can track thousands of tasks, teams, calendars, and other pieces of work progress data autonomously to constantly surface the parts of complex projects – or a portfolio of them – that need immediate human attention.
It was once so difficult to deliver complex projects on time that most failed. Moovila’s task-specific AI is changing that outcome, making on-time delivery and revenue recognition – across a wide range of industries, from construction to IT – easy to achieve. With automatic monitoring and management, even the most complex projects stay on track.
What can AI do to help improve your profits? That is a question worth tackling.
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