It seems like everyone in the business world has a strong view on how and when organizations should implement AI. At one end of this discussion are tech evangelists who understand the benefits of AI and are pushing for adoption immediately, sometimes without creating proper risk management strategies. At the other end of the debate are skeptics who remain fearful of potential risks in spite of the obvious benefits.
As AI matures and the pressure to adopt continues to increase, decision-makers find themselves caught in the middle of this heated debate, unsure of where to stand. Should they embrace AI wholeheartedly, seizing its promises of increased efficiency, productivity, and innovation? Or should they proceed with caution, mindful of the risks and unintended consequences that AI may bring?
These are big questions that don’t have easy answers. Let’s discuss the multifaceted considerations and diverse approaches that organizations are employing as they navigate the landscape of AI adoption to shed light on the challenges and opportunities that lie ahead.
Real Risk, Great Reward
Even as questions about the risks of AI hover around the industry, generative AI tools have continued to receive huge amounts of attention and support, including billion-dollar investments from companies like Amazon. This suggests that, while the future of AI remains to be written, its effects are still expected to be transformative across many different industries. McKinsey, for example, claims that AI could increase corporate profits by $4.4 trillion a year.
But those profits don’t come without risk. AI models are trained on, ingest, and produce lots of sensitive data, and organizations that use AI must make sure that all of this data remains secure. This is a source of anxiety for many leaders due to the evolving nature of the new technology, and indeed, researchers are still learning more about potential vulnerabilities to AI systems. Firms can limit their liability and protect their users and customers by working with a provider who has a proven track record on cyber security, including important industry-standard security certifications like SOC 2.
Still, while AI will create new data vulnerability issues that organizations must address, it’s important to remember that it will also boost profitability by enormous margins, which is why today’s leading companies are rapidly adopting AI with an appropriate level of care. In fact, according to a recent study by AvePoint, AI is already widespread in the United States, with 74% of companies using it. Those who successfully contain the risks of AI stand to reap great rewards.
Duality of Opportunity and Bias
AI has the power to do real social good by eliminating human biases and flattening barriers to opportunity in crucial areas. AI assistants, for example, could provide a low-cost, effective way of delivering advice and care to communities that currently lack access to reliable healthcare and legal services. While real-life use cases are still evolving, researchers and entrepreneurs believe that AI can also help drive equity in recruiting, government, and other key sectors. But even as AI is being used by innovators to help solve important social problems, some have sounded the alarm bell about potential threats to human interests.
AI skeptics point to a cluster of issues related to bias in AI systems. Some of these problems—like endemic racial and gender biases in some AI training data, for example—are well-documented and known to members of the public.
While AI certainly can help people and society at large, emerging issues with bias have reminded the public of some of the pitfalls of lax management and development.
Here, the conversation turns to the integrity, security, and composition of both user and enterprise-level data, which is crucial when it comes to limiting the potential risks of AI to people and organizations alike.
To make sure that bespoke LLMs and other purpose-built AI products do not contain racial, gender, or other biases, for example, IT leaders should carefully regulate and eliminate any such biases from the data that they plan to use to train their models. When training data is sensitively managed, AI output is much more effective and much less likely to expose companies to reputational harm or risk. As with any new technology or business venture, it’s impossible to completely eliminate risk, but proper management and robust safeguards can go a long way toward making this new technology safe and effective for everyone.
Balancing Productivity and Privacy
It’s no secret that AI is expected to completely transform the way we work, leading to employee productivity gains of up to 66%. But as companies look to turn the promise of AI into real activity, it’s critical to be mindful of potential threats to customer and user privacy, which is one top concerns reported in the AI & Information Management Report.
When it comes to safeguarding user privacy, data again takes center stage. Because AI models intake, maintain, and produce huge amounts of sensitive information, the protection of user privacy is also closely related to data security, particularly with regard to things like user input. An employee at a large organization like a bank, for example, might have to feed confidential information to an AI model in the course of their daily work. If that model’s inputs are not properly secured, this could expose the institution to huge legal and financial risks.
Organizations can manage this risk by developing clear and practical policies. They should also be particularly thoughtful about when and how they store and secure user input to AI models. In many cases, this safeguarding will require the support of an external vendor or consultant.
To ensure that AI tools are used and deployed in a manner that does not cause harm, organizations need to develop and enforce well-defined policies to govern the use, development, and implementation of AI. It’s completely feasible to reap the benefits of this new technology while protecting user and customer data, but this requires a balanced approach. Instead of thinking of the issue as an either/or choice between secured privacy or enhanced productivity, leaders should understand that privacy is not fundamentally at odds with increased efficiency. It’s possible to advance all stakeholder interests with a single strategic position.
With AI, the Benefits Greatly Outweigh the Potential Liabilities
The benefits and potential drawbacks of AI have received a lot of public attention. While AI skeptics are right to raise legitimate questions about topics like user privacy and data security, decision-makers shouldn’t let these issues stop them from moving forward with an AI strategy.
As the AI revolution continues to mature, the biggest winners will be those who use AI in the smartest way possible, which means the organizations that appropriately balance potential risks against potential rewards. Instead of approaching AI adoption as a choice between risk on one side and reward on the other, leaders should think about how they can limit liability while maximizing benefits; well-crafted strategies can satisfy both sets of needs.
Continue the conversation. Listen to Navigating the AI Revolution: Challenges and Opportunities in the Digital Workplace for more insights on AI's risks and rewards.
