(This article is part of a series on Artificial Intelligence for Board Members and Senior Executives.)
Artificial intelligence (AI) is a double-edged sword that presents as many risks as it does opportunities. AI can transform business, revolutionize processes, enhance efficiency, and drive innovation. Organizations actively embrace AI for customer service, sales and marketing, predictive analytics, and more. AI can also present new, unforeseen challenges..
The potential risks posed by AI are very real and can disrupt operations and create chaos that is damaging and costly. However, the biggest risk of all is the risk of disruption should you not actively engage AI within your business.
Let’s start with a closer look at each of these risks.
Potential Risks from AI
New Cybersecurity Risks
AI gives hackers new sophisticated tools, especially with new open-source AI technology. We see more cybercriminals, especially foreign bad actors, harnessing AI to generate highly effective phishing campaigns and cyberattacks. Since OpenAI released ChatGPT in November 2022, there has been a 1,265% increase in phishing emails.
One of the biggest challenges is deepfakes. Using AI, hackers can impersonate anyone, including CEOs and decision-makers. Take the case of the Hong Kong finance worker who was tricked into paying out $25 million because of deepfakes. The worker was suspicious when he received an email, purportedly from the CFO, asking for the release of funds, but the clincher was when the worker joined a Zoom call that showed the CFO and his colleagues. The worker was the only human on the Zoom call. The others were all an AI-generated deepfakes.
We are entering into an AI arms race where we need AI-powered solutions to protect us from hackers using AI. Ensure your security vendors are using the latest AI technology and that your management team understands the potential threat posed by AI.
AI Risks to Corporate Reputation
AI can put corporate reputations at risk if not properly implemented and monitored.
Take the case of Air Canada, which damaged their reputation due to the way they handled an AI-powered customer service glitch. A passenger traveling to attend a family funeral failed to ask for a bereavement fare, so when they went back to Air Canada to request a reimbursement for the discount, the AI-powered chatbot told the passenger, “No problem.” There was a problem, however, since Air Canada’s policies clearly state that a discount must be requested before travel. Air Canada chose to fight the case in court, rather than provide the small discount requested. Fighting the case in court damaged Air Canada’s reputation.
Be careful where and how you deploy AI tools and be diligent about monitoring their performance. More importantly, consider the impact on your reputation when handling issues related to AI.
AI Can Present Legal Risks
Like any technology, AI is imperfect, and those flaws can lead to legal issues.
For example, Hello Digit, a financial technology company, was supposed to save customers money and guarantee no overdrafts. A faulty AI algorithm resulted in the company pocketing a portion of the interest and overdraft fees and penalties for customers. It also led to the Consumer Financial Protection Bureau (CFPB) taking action against Hello Digit. Hello Digit will likely have to defend their AI solution in court.
AI enables some fantastic things, but just because AI can do it doesn’t make it legal. For example, Facebook (now Meta) AI facial recognition technology can identify people in a photo with you. What sounds completely innocent – here you are in a photo your friend took – actually violates Illinois’ biometric privacy act. The settlement cost Facebook $650 million.
AI Can Pose Operational Risks
Automated operational processes using AI require management oversight and a consideration of human behavior as well.
In 2021, Zillow’s stock price plummeted mainly because they relied on a faulty AI algorithm to predict house prices. Zillow was purchasing houses based on those predictions. AI can be a powerful tool for predictive analytics, but even AI can only make predictions based on historical information. Events like the COVID-19 pandemic are sure to skew predictive analytics, and did so to the detriment of Zillow.
Any operational change must also consider the human factor. People must embrace new AI processes. For example, UPS developed ORION, an AI-powered platform to route packages and trucks. But for Orion to work, UPS had to convince workers to adapt how they worked to the new system. At first, employees didn’t like adapting. It took time to get employees to use the new AI-powered procedures. Ultimately, Orion reduced fuel and maintenance costs and enables drivers to make more deliveries. However, ORION almost failed because employees didn’t really want it.
Risk of Disruption
The greatest risk of all is not aggressively adopting AI when your competitors are.
According to IBM, 42% of enterprise-scale organizations have deployed AI, and 40% are exploring AI adoption models, including 59% that have accelerated their AI investment.
AI is already dramatically impacting sales and marketing, product development, service operations, and supply chain management. Companies that fail to leverage AI to create a competitive advantage, risk falling behind (see “AI’s Competitive Advantage”).
AI Opportunities Provide a Competitive Advantage
To use AI to the best competitive advantage, organizations must determine where artificial intelligence can yield the greatest returns (see “CEO’s Guide to Generative AI: Proactive Advice for 2024”).
McKinsey’s research shows generative AI use cases usually fall into four areas: customer relations, sales and marketing, software engineering, and research and development.
Here are some of the most promising areas of opportunity presented by AI for organizations:
- Sales and marketing – AI is improving marketing and increasing sales by enhancing customer engagement. For example, Capgemini uses an AI platform to track buyer intent through the sales funnel, increasing the number of qualified leads five times. Starbucks uses AI to analyze customer data to customize offers and apply dynamic pricing to increase customer loyalty and average order value.
- Product development – AI is invaluable in predicting customer desires and behaviors, making it ideal for product development. Stitch Fix uses AI to curate personalized outfits for customers, analyzing preferences, fashion trends, feedback, and other factors to customize outfits and influence inventory decisions.
- Service operations – AI can facilitate customer service. For example, Unilever’s AI system reduced customer service response time by 90%. Companies also use AI for predictive analytics for applications such as scheduled maintenance. GE Aviation, for example, had reduced unplanned downtime by 50% and saved $1 billion in maintenance costs.
- Supply chain management – As the UPS example shows, AI can optimize shipping and logistics. Maersk uses AI for real-time shipment tracking, making it easy to alert customers in the event of delays. Delly’s Food Service in Brazil uses AI for dynamic pricing optimization, increasing their gross margin by 1.1% (a huge amount in a low-margin business) by managing changing market prices.
Any organization that wants to compete in today’s market will adopt AI, but C-level executives must keep their eyes open. While AI has risks that need to be managed, AI can yield tremendous benefits, giving any company a competitive advantage over larger competitors.
If you care about how AI determines the winners and losers in business, how you can leverage AI for the benefit of your organization, and how you can manage AI risk, contact me at glenngow.com. I write and speak about how senior executives, board members, and other business leaders can use AI effectively. You can read past articles and be notified of new ones by clicking the “follow” button here.
