AI is both a boon and a curse for small businesses. Cheaper technology means more minor players can level up their competitiveness without rapidly scaling up, but the technology's reliance on data raises many privacy concerns. This isn't all that surprising. Recent news has been dominated by stories of data breaches that undermine trust and force organizations to take drastic action to prevent further damage.
There is more data showing that small and medium-sized businesses are successfully walking the tightrope between embracing exciting new technology and approaching the mysterious AI with caution. Earlier this year, Zoho partnered with Michael Fauscette and Arion Research to conduct a global privacy and AI study titled “The AI Privacy Equation – Balancing Innovation and Protection in the Modern Enterprise.” The study surveyed 4,782 business professionals around the world, 47% of whom were small to medium-sized businesses. Furthermore, 33% of the companies surveyed have fewer than 100 employees.
The findings, released in September, paint a complex but ultimately optimistic picture of how small and medium-sized businesses are venturing into the uncharted territory of privacy. Ultimately, companies understand the privacy risks posed by AI and are taking steps to get ahead of it and avoid it. And research shows that companies that put the right focus on privacy are poised to create a sustainable competitive advantage.
Here are some facts from the survey and what it means for small businesses.
“When surveying organizations about their privacy concerns, customer data breaches account for 40.8% of the top responses.”
According to the study's summary, “This primary focus reflects the reality that breaches of customer data carry the highest potential for reputational damage, regulatory penalties, and business interruption. Organizations understand that customer trust forms the foundation of business relationships, making protecting customer data a top privacy priority.”
While large companies can try to perform damage control when data privacy issues arise, small businesses don't share that luxury. Their resources are too thin and the competition for customer attention in the first place is too fierce. News about the problem spreads quickly and can derail small businesses that would otherwise be launched.
Rather than acting reactively, small business owners need to be proactive and address privacy concerns before they become reality. This process begins by codifying your data privacy stance, publishing it on your company website, and sharing it widely. Once in place, prospective customers will be able to compare policies with other companies when conducting exploratory research, meaning these privacy policies will become a competitive differentiator. It is much easier for small businesses to assert their data privacy rights than, say, to promise a huge customer service team or the latest flashy technology.
It is also up to small businesses to address the other two major concerns identified in the privacy survey: employee privacy (18.6%) and regulatory compliance (14.6%). Fortunately, the approach doesn't have to be that different. By creating data privacy policies for their customers and publishing these policies online, small businesses demonstrate to their employees that they take data privacy seriously (perhaps even include them in the creation of their privacy policies) and provide a framework for building mechanisms to maintain compliance.
“Rather than weakening privacy protections, 41.3% of organizations have significantly strengthened their privacy practices since deploying AI technology, and a further 25.5% report that they have somewhat strengthened their approach to privacy.”
It may seem counterintuitive at first that increased adoption of AI will lead to stronger privacy measures. At the end of the day, much of the privacy conversation revolves around how AI has complicated the privacy formula, with little understanding of the technology and even less regulation and governance.
But as the study highlights, the process of implementing AI requires companies to take a deep look at internal best practices. These need to be fully fleshed out so that they can be expressed in AI large-scale language models (LLMs), allowing new AI technologies to operate within the right context and best serve your business. Often, in the busyness of simply trying to keep the lights on, small businesses abandon formalizing certain processes and continue business as usual, believing that there comes a time when looking at the bigger picture makes the most sense. The implementation of AI will force such thinking in the nearer future.
It is heartening to see companies increasing their knowledge of AI as AI technology rises. The study found that 37.2% (5 out of 5) of companies surveyed strongly agreed (5 out of 5) that they clearly understand the privacy implications of their AI systems, and 33.9% said they mostly agreed, giving them a rating of 4 out of 5. This shows that rather than viewing AI privacy as an insurmountable challenge, companies are confident in their ability to venture into uncharted territory. If small businesses are to succeed in the future, they must meet this challenge head-on. Rich analytics and data can aid these efforts by providing information about each step of a company's workflow, especially when analyzing risk. For example, the study found that companies correctly identified recording customer calls, training AI models on customer interactions, and remote working as the three aspects of business with the highest privacy risks. Focused analysis on these three operational areas ensures that your privacy efforts are targeted for maximum effectiveness and strengthens key points where exposure can occur.
“Organizations face three main barriers to successful AI implementation: privacy and security concerns (37.2%), lack of technical expertise (36.6%), and cost concerns (32.3%).”
Not surprisingly, the second and third most prominent barriers to enterprise AI adoption are skills gaps and high costs. But what's a bit surprising, and reassuring, is that the main causes of suspension are related to security and privacy. This, of course, shows that companies are taking these topics seriously.
As mentioned earlier, it is unlikely that small businesses will be able to avoid AI completely. This means these companies need to start focusing on upskilling their employees, if they aren't already. These people need to learn how to get the most benefit from AI tools and how to interpret their output to make more informed business decisions.
Fittingly, the study found that companies are prioritizing data analysis and interpretation skills (55.7%), AI literacy and understanding (47.1%), and agile engineering capabilities (39.6%) in their workforce development efforts. The emphasis on data analysis skills indicates that AI effectiveness requires high-quality data management and interpretation abilities. Organizations that actively invest in these foundational skills create a sustainable competitive advantage in AI implementation.
Even small businesses would be forgiven for feeling that the above levels of technical knowledge far exceed the demands they place on their employees. But with nearly every competitive landscape undergoing rapid revision, it's always helpful for companies to learn more about what they don't already know in order to minimize unexpected disruptions. Research lessons on interfacing with AI can also ease the transition to new technologies in the future.
The conclusion is
The AI Privacy Equation global survey provides even more promising data points. This shows that all businesses, not just corporate organizations, need to focus on privacy. Businesses of all sizes understand that while AI is a powerful tool when used ethically and sustainably, the risks of getting it wrong are very high.
Ultimately, what small businesses should take away from this research is that AI privacy is not a one-and-done solution. Instead, companies must continue to adapt to changing circumstances around them. This research suggests that organizations are tackling this challenge head-on and understanding the right investments to make along the way: prioritizing people, processes, and governance structures to ensure AI can gain a foothold without becoming overly invasive.
As with most things, patience is a virtue in AI privacy.
