Artificial intelligence is transforming how businesses make decisions and develop products. The global AI market is expected to grow to $1345.2 billion by 2030, and many businesses are leveraging AI to streamline and improve their product roadmaps.
However, as a newer technology, there is some hesitance to adopt AI or skepticism over its capabilities.
In fact, when Sprig launched our AI Analysis tool, some of our users expressed skepticism that AI could accurately summarize results. We handled this skepticism head on by answering any questions from our customers and explaining how the technology was built to ensure accuracy.
Here, we’ll share ways to overcome AI resistance so your team can build a better product and grow your bottom line.
Why is there resistance to AI?
Concerns about its abilities
As more AI tools enter the mainstream, more platforms are making bold claims about their transformative powers. This messaging leads to a healthy amount of skepticism — can AI truly deliver on its big promises? As a result, some businesses are hesitant to adopt these tools.
Challenges in implementing AI
Stubbornness, inflexibility, and an unwillingness to try new strategies may prevent your teams from seeing AI’s potential.
Implementing AI also involves some technical challenges. Adopting new processes and tools takes time, expert guidance, and resources to make it all work. These challenges can slow team progress and make them feel less confident in the power of AI.
Job security
Though AI has been around for a while, it entered the public discourse with generative AI tools that create art, hyperrealistic content, and similar applications. This led to larger discussions about AI’s role in society. As this conversation developed, it inadvertently fueled a fundamental misunderstanding of AI’s true purpose: to help humans, not to replace them.
Because AI can automate tasks and complete tasks more quickly, there are concerns that it will replace human workers. Around 60% of workers who use AI report worrying about its impact on their roles. With this concern on the line, it’s even more important to emphasize that AI is for assistance, and that it’s not intended to supplant an employee’s full role.
AI adoption strategies your business can use
Make transparency and trust a top priority
Addressing concerns about incorporating AI in your business begins with complete transparency and consistent communication. Make sure your teams know how your company leverages AI, from the tools used to its role in product development to its impact on decision-making. By being transparent with your team, you show that your company is committed to ethical implementation of AI.
Invest in education and training
After transparency and trust comes education. You’ve explained how AI can benefit your organization and how you’ll use it responsibly. Now, teach your teams how AI works. Demystifying AI will make it easier to incorporate into everyday tasks.
AI training sessions, workshops, and company resources should be specifically designed for each department within your company. For example, your product team may need in-depth training on the AI program you’re implementing, while executives likely only need an overview of how it works. Make sure that your AI educational resources are tailored thoughtfully for each audience for the most effective results.
Start small and scale gradually
To manage skepticism and overcome AI resistance, it’s best to utilize AI with smaller projects first. Successfully using AI with a small-scale project can demonstrate its value and instill confidence in your teams.
For example, you might use AI to evaluate one set of survey responses regarding a new product feature. A tool like Sprig’s AI Analysis can examine responses and uncover insights like bugs, reasons for user behavior, and strengths in your product. From here, you might use AI to interpret customer feedback for other features. Or, work AI into one product experience workflow and evaluate the difference it has made compared to manual tasks.
Three AI business success stories
Building a customer-centric product with AI
Ramp, a modern finance platform, automates finance operations to help build healthier businesses. Their product operations program consists of three main tenets: enabling launches, optimizing for scale, and uplifting the voice of the customer.
The last tenet was particularly important to Ramp, especially as the company grew. “At Ramp, it’s essential for the customer to be an active part of the product development process,” said Read Ward, Product Operations Lead at Ramp.
Ramp used Sprig in-product surveys to target the right users at the right time. Thanks to Sprig, Ramp received more than 10,000 survey responses and improved its NPS program. With Sprig AI, Ramp evaluated all of the feedback and identified key insights, saving its product team hours of manual work.
Now, Ramp has a solid customer-centric program for improving their product with Sprig. Ramp uses Sprig to send targeted surveys, synthesize the responses, share insights, and make improvements.
Using AI to dig deeper into user feedback
Noon Academy is a peer-based e-learning platform for grades seven through 12 that relies on social engagement. One of its new social features is peer-based study, which allows students to break out into small groups independently.
One of the biggest challenges in evaluating the performance of this new feature was language. Noon Academy needed an easy, efficient way to gather feedback and insights from students in eight countries and in multiple languages.
Sprig AI Analysis helped Noon Academy filter through survey responses quickly and pinpoint themes. They saw that overall satisfaction differed significantly from country to country. When they dug deeper into the open text responses from a specific country, two themes emerged. The first involved bugs in the program. The second revealed that users needed guidance to properly use the study groups feature.
Using these insights gained with Sprig, the design team made feature updates to help students participate in groups. Noon Academy saw their user engagement increase almost immediately, with a 74% increase in participation and a 192% increase in social interfacing.
Turning survey responses into product recommendations with AI
Coinbase, a cryptocurrency exchange platform, wanted to make filing taxes as easy as possible for their users. Documenting users’ financial information for tax season is one of its core services, and Coinbase wanted to make this interface better for users.
To do that, Coinbase needed to understand general audience feedback and customer behavior. But they also wanted to segment feedback based on more advanced user needs. Coinbase used Sprig’s AI Analysis to dig deeper into their survey responses and learn more about their tax center users.
Coinbase ran a CSAT survey to see why their users were visiting the tax center. AI Analysis found that they wanted simplified tax reporting but had trouble downloading tax documents. Frustration and confusion with the interface led to negative sentiment toward the platform.
Thanks to qualitative feedback and helpful AI analysis, Coinbase eliminated bugs in its tax center and made tax filing easier for its customers.
Overcome resistance and implement AI the right way
AI can be used to synthesize massive amounts of data, glean insights from data, and help teams act on those insights. Furthermore, businesses can use AI to stand out from competitors and stay ahead of the game.
Sprig’s GPT-powered AI Analysis can help businesses create high-quality products and next-level customer experiences. With Sprig AI, you can filter user feedback and better understand customer data — without the manual work of compiling and evaluating surveys. Fix bugs and improve your product in a fraction of the time with Sprig AI.
Get started with Sprig today.
