Craig Walker is the Founder & CEO of Dialpad. He has 20+ yrs experience as an entrepreneur, venture capitalist, tech executive and attorney.
The adoption of artificial intelligence is running into barriers within businesses—but not for the reasons you might think. Despite all the headlines about AI-driven job losses and disruption, professionals in customer service and sales are mostly optimistic about its impact. A bigger obstacle appears to be perceptions of AI’s high cost of implementation and a lack of clear, company-wide policies governing AI’s use.
These are among the findings from my company’s annual State of AI at Work Report, which surveyed over 1,000 sales and customer service professionals at various seniority levels across a wide range of industries.
• Some 70% of respondents said they aren’t scared of AI stealing their job, and 79% of those who are using AI said it had a positive impact on their performance.
• Even so, 84% of respondents—including over half of those whose company is already using the technology—said their employer lacks company-wide AI policies.
• Over a third (37%) of respondents said a lack of funds was preventing more AI adoption.
To me, the survey findings underline both how far and how fast we’ve come on the AI journey—and how far we still have to go. They suggest many businesses are feeling stuck over how to invest in generative AI capabilities, daunted by overly pessimistic views on its complexity and expense.
Yes, AI solutions can be costly and complex, making them an intimidating prospect, especially for smaller firms. (The survey found that 52% of companies with under $100 million in revenues see AI as inaccessible.) But the truth is that most companies don’t need to reinvent the wheel to reap significant benefits from AI.
To start, they should be thinking about where they can get the greatest impact by applying AI tools to enhance specific areas of their business. Then, they should look for out-of-the-box products that come with the costs and complexity baked in, and that can just plug into their existing systems. Not only is this more cost-effective, but it can also make life easier for internal IT teams and encourage higher adoption from the employees and end users—which in turn helps them maximize the benefits of using these AI tools.
Customer service, sales operations, recruitment and internal collaboration are all examples of functions where generative AI can have an outsized impact at a relatively low cost. We’ve seen countless customers deploy AI in these areas with intuitive, easy-to-use tools that employees can adopt quickly, no matter the size of the business.
For example, AI sentiment analysis now makes it possible to obtain customer satisfaction (CSAT) scores from every call, which provides a much more holistic understanding of customer satisfaction compared to the traditional survey method.
AI also empowers sales and customer service employees to manage their own development—another important, but overlooked, way in which AI can even the playing field for employees. AI-powered feedback during and after calls helps agents see exactly how to improve their performance for the next interaction before their manager has to step in to tell them. It can also sharply reduce the amount of “busy work” that distracts agents from more valuable tasks—a benefit of AI that was cited by 47% of survey respondents.
One reason AI implementation can be so expensive is that many providers bolt on parts of their offering, such as server capacity and transcription, from third-party vendors and then pass on those costs to clients. That’s why it’s usually better to opt for providers with full-stack integrated solutions that better enable them to control costs.
Companies shouldn’t have to make exorbitant investments in technical expertise or training to benefit from AI. The key is to choose the AI tools you use wisely, taking into account factors like ease of use, the trajectory and stability of those providers and whether they are built in-house. As more businesses understand this and experience the productivity gains from AI, I believe the barriers currently holding back wider adoption will fade away.
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