Let’s Leaven the AI Hype with a Healthy Dash of Realism
It’s time to leaven the AI hype with a healthy dash of realism, and in doing so, get rid of unrealistic expectations around AI.
A little bit of magical thinking sprinkles some excitement into the workday. Perhaps that’s why AI hype spread like wildfire throughout enterprises in recent years, leading otherwise rational people to think that nearly anything would be possible with AI, and that all it would take is the wave of a magic wand to usher in this fantastical new world.
Alas, the reality is a bit of a different story. And that’s a good thing.
It’s time to leaven the AI hype with a healthy dash of realism, and in doing so, get rid of unrealistic expectations around AI. Instead, let’s replace them with an understanding and appreciation of the real-world things that AI can accomplish and the areas where it can deliver success – because these areas are growing every day.
What Exactly Is In Those Contracts?
Let’s start with contract intelligence. The ability to understand the contents of mountains of contracts at a deep level – including what clauses they contain, what type of risk they might expose the organization to, or what opportunities they might reveal – is a useful goal in any age.
But in the environment that has taken shape in the past year, as COVID-19 and its associated lockdowns have turned the world upside down and created precarious economic conditions, this capability has only gained in importance.
After all, who wants to be blindsided by clauses that might leave them on the hook for costs that in “normal times” they never would’ve expected to come their way? (That tapping sound you’ve heard over the past seven months is a million different executives Googling “force majeure”).
Aside from risk, contracts might be hiding opportunities, which is an equally compelling reason for contract intelligence. For example, there might be a fee that you’re contractually entitled to charge that you haven’t bothered to implement while the economy has been on solid footing. Now that more uncertain times are here, it might make sense to start enforcing that charge and solidifying your balance sheet.
Painstakingly reviewing an entire contract portfolio is a time consuming – not to mention expensive – a proposition that requires an army of bodies. This is precisely the type of real-world task that AI excels at.
AI – which is powered by human-trained models; let’s not forget that the robots are not coming to replace us – can efficiently scan contracts and understand what clauses and provisions they contain. In this way, AI surfaces the risks and opportunities within them, helping to deliver contract intelligence in a cost-efficient manner.
Knowledge Management Made Easy
Knowledge management is another one of those real-world areas where AI can deliver real value, today.
Having deep knowledge about your clients and projects, what best practices documents are available as resources, and where expertise lies within the organization is essential to running the organization as efficiently as possible – something that COVID-19 and the uncertain economy has placed a premium on.
AI automates the curation aspect of knowledge management, automatically surfacing expertise and best practice documents. Simply by analyzing various signals and pieces of data, AI can identify, for instance, who within an organization has expertise on European property law, or which share purchase agreement template has been viewed and downloaded the most times and is best suited to serve as a starting point for new projects.
This is next-generation knowledge management, powered by AI.
Making It Happen
To start heading down the road with AI in areas like the above, organizations are realizing that in addition to adjusting their expectations to a more realistic tenor, they need to focus on “the basics” – aspects like change management and people management. People, process, and technology all need to work together for any project to be successful, and AI is no exception.
Additionally, organizations need to be very clear on what problem they’re trying to solve with AI.
Let’s briefly revisit our magical thinking from before.
Are you deploying AI for a vague and overly ambitious goal like “transforming all aspects of the business”?
Or have you zeroed in on a very specific application, like contract intelligence, or knowledge management?
Just as expectations around what AI can and cannot do should be tethered to reality, so too should the manner in which success is measured for AI initiatives. For instance, if AI can help an organization reduce revenue leakage in its contracts by 5%, that might seem like an unimpressive number. But if that translates into millions of dollars per year, it’s a success.
AI is a long game. Those questioning the value of this technology should take comfort in the fact that the hype portion of the lifecycle – and the unrealistic expectations that come with it – has started to fade away. In its place, there is a realistic understanding of what AI can do, paving the way for organizations to tap into this technology in very specific and powerful new ways.