Are you an AI company or a company that leverages AI? -

Panache Ventures' Scott Loong talks about why startups shouldn't reinvent the wheel.

Investor Deck is a six-part article series from Sage featuring tips from Canadian VCs for SaaS startups. You can find the previous article here.

Artificial intelligence has been a hot topic in the tech industry for the past 18 months, creating an identity crisis for many SaaS startups.

As investors pour more money into AI businesses, many startups Become AI company.

“There seems to be a perception that sometimes it's true and sometimes it's exaggerated that AI is still inaccessible because of either a talent gap or a knowledge gap, but I don't think that's generally true.”

Scott Luhn, Panache Ventures

But these pivots are often unnecessary and doomed to failure, says Scott Loon, a partner at Panache Ventures who spends a lot of time trying to determine whether companies are AI-native or AI-enabled, and says it's a distinction more founders need to consider.

“No one needs to be convinced that these products are powerful,” he says. “The incentives to adopt them are very high.”

But as businesses accelerate their shift to AI, Loong believes SaaS leaders need to think about what they can do with the resources they have.

“The question a lot of startups are asking themselves right now is, what do they have access to, given their existing engineering team?” he said.

Loong, who is no stranger to the space having founded and exited his own AI and insurtech startup, believes startups that don't offer AI as a core product should not try to reinvent the wheel to stay competitive.

“There's a perception that AI is still inaccessible, either because of a talent gap or a knowledge gap, which is sometimes true and sometimes exaggerated, but generally I don't think it's true,” Loon added.

Building and running large-scale language models is an incredibly expensive endeavor, requiring specialized chips, lots of computing power, and highly skilled engineers. Creating a bespoke AI solution from scratch might seem like it would provide a competitive advantage, but Loong believes that for most startups, it's simply not necessary.

For most startups from seed to Series A, off-the-shelf AI tools will be enough to achieve their goals, and buying or licensing these solutions can be more practical and cost-effective than building them from scratch, Loong said.

“Take a typical B2B SaaS company, for example, and you don't have the resources or the need for very sophisticated in-house AI knowledge,” he says. “In that situation, you have to look for low-hanging fruit in what's currently being done by a few individuals in a tedious way.”

Eric Sleeth, senior product marketing manager at Sage, said the rise of AI is creating the same hype as cloud did 10 years ago, and he agreed with Loong that leaders should focus more on the business problems that AI can solve.

“AI is a resource multiplier.”

Eric Sleeth, Sage

“Startups thrive on innovation and efficiency, and AI accelerates both,” said Slees. “AI is a resource multiplier, increasing productivity and reducing operational costs, allowing startups to scale rapidly without proportionally increasing their workforce.”

For example, accounting and finance teams often spend a huge amount of time on tasks like data entry, budgeting, reconciliation, creating reports, analyzing data to forecast future events and make business decisions, etc. These are all functions that can be easily automated with AI, yet according to a 2023 report, more than 60% of finance executives are not using AI yet.

Sleeth noted that finance teams are especially plagued by rigid financial systems and lengthy processes, and are well-suited to be transformed by AI. “The superpower of a SaaS startup is to be agile and innovative,” he said, adding that AI will enable finance teams to operate more like startups.

Sage designed its AI-powered Copilot solution to help finance leaders, accountants, SMEs, and HR leaders automate tedious tasks, freeing up leaders' time to focus on improving their business.

The solution uses adaptive learning algorithms to analyze each business process and decision-making pattern, and also has built-in natural language processing capabilities, making it ideal for SaaS startups without in-house technical expertise.

Meanwhile, Sleaze believes finance teams are “begging” for more value-added work, rather than being overwhelmed with manual, time-consuming tasks.

“AI can free up human resources, but this is just the beginning,” Sleeth added. “More sophisticated finance teams will begin to use AI to augment human capabilities, such as monitoring compliance, detecting anomalies, and providing deeper insights into financial performance, customer behavior, and market trends.”