Artificial intelligence: It might seem like a far-fetched, futuristic idea that only applies to companies building robots, self-driving cars or supercomputers, but in fact, AI is an increasingly common business tool that can be used by companies of various sizes and sectors.
As the cofounder of a venture capital firm that invests in automation and AI companies, I’ve seen that whether you run a startup or a large multinational organization, AI software can help your company achieve higher productivity and profitability.
Understanding The Value Of AI
Before we dive into three practical tactics for investing in AI, it’s important to define exactly what AI is since it’s a term often thrown around in many different guises. At a high level, AI is a broad category of intelligent software that can enable computers to “learn” from themselves and one another. AI includes the sub-category of machine learning, which is a broad set of algorithms that enable computers to make predictions or decisions by analyzing a massive amount of structured and unstructured data.
The world is awash in data. In 2020, roughly 64 zettabytes were created, captured and consumed worldwide, and by 2025, that number is expected to rise to more than 180 zettabytes. (To put this into perspective, one zettabyte is equal to roughly a trillion gigabytes.) All this data is incredibly valuable, but only if organizations can understand and act on it. Companies that effectively analyze and make decisions based on data will be the clear winners in the next decades.
And that’s where I believe AI comes into play. AI enables computers to understand data to make forward-thinking predictions. Some of the industries making early strides in deploying AI include healthcare, logistics, e-commerce and financial services, as companies in these fields live or die based on their ability to understand and quickly act upon data patterns. But all companies, in every sector, are increasingly reliant on data analytics to build products, better serve customers and understand their business trajectories.
So what are some concrete steps you should take as a company leader to ensure you’re investing in the AI solution that’s right for your organization? Here are three tips to get you started:
Do your research on startups.
When it comes to AI software, bigger, established companies aren’t necessarily better. Today, I believe the true innovation in AI and machine learning is coming from startups.
The AI 100 list of high-growth startups is a good place to start when looking for the most innovative AI technology providers. It lists top-performing AI startups serving many different sectors. As an investor in AI startups for the past decade, I’ve seen the performance and accuracy of these systems increase dramatically while costs have plummeted, thus making valuable solutions more affordable and widely available than ever.
That said, when approaching any AI startup to see if their solution might be a fit for your company, you should ask a few key questions, including: Are they focused on your industry? And can they scale to serve your business? I also recommend explicitly asking for other user or customer references. You can use this information to determine how committed the startup is to your profile as a customer; how they built their AI models and how large of an engineering team they have in-house (along with how much development was done in-house vs. using off-the-shelf AI platforms and application programming interfaces).
You can even ask the startup to share case studies from actual customers showing the measurable results they’ve achieved. When you do this, listen for whether the startup is focused on delivering a tangible and measurable return on investment to customers.
If you’re investing in synthetic data, ensure the solution is tailored to your industry.
One AI technology I’ve seen growing interest in is synthetic data. My firm has invested in companies in this space, and through this experience, I’ve seen that despite the high volumes of data we create every day, there’s still not “enough” data for every company to truly understand their market, competitors and business prospects. This is because data is a record of what already happened, not what might occur. And for some brands, that’s now where synthetic data comes in.
If this is a solution you’re considering, ensure the synthetic data provider specializes in your industry. One company my firm has invested in, for example, specifically works with brands in healthcare, finance, real estate, and logistics to create and analyze synthetic data to make better business decisions. I also suggest asking to see results of how the technology will impact your bottom line.
Make a plan for how you’ll maximize AI’s potential.
When it comes to AI, its twin is automation. Robotic process automation software can help drive efficiency by learning and executing data-processing tasks currently performed by humans. AI-driven RPA software can also liberate humans to focus on creative tasks, such as finding innovative solutions to business problems.
From my perspective, for any company looking to invest in AI software today, it’s critical to also consider how you plan to leverage the intelligence gleaned from that software to automate business processes. That might simply mean automating billing operations, or it might mean automating something physical, such as logistics in a warehouse.
AI is no longer the stuff of science fiction. For every company in every sector, AI can help deliver critical insights and streamline processes. For founders building companies, deploying AI software can be the competitive differentiator that sets your business apart from the fray.
Source: forbes.com
