Those who buy into the explosion of hype around generative AI will think this flavor of artificial intelligence is the best thing to happen to computing since cloud storage. However, you may be under the wrong impression.
As businesses and industries continue to evaluate the pros and cons of ChatGPT, generative AI, and other forms of artificial intelligence, some adopters are extolling its time-saving and innovative benefits. Some people are hesitant to trust new technology. In any case, there is ongoing debate about where the AI generation is headed.
In January, Talkdesk published a report warning that persistent bias and inaccurate data are permeating retail experiences that already integrate AI, impacting consumer attitudes towards new technology. did. The idea comes as shoppers record runaway AI-powered interactions and worry about how companies use facial recognition, customer data, and common unethical AI use cases. Was born.
According to the Talkdesk Bias & Ethical AI in Retail Survey, shoppers are already dissatisfied with their customer experience and are ready to walk away from brands that don't practice responsible AI use. At the same time, corporate insiders rave about how targeted their AI results are and get excited about how sharp everything is and badmouth each other.
The mixed feelings may not portend an acceleration in the expansion of artificial intelligence this year, as some advocates predict. Shannon Flanagan, vice president and general manager of retail and consumer products at Talkdesk, said the report represents a shocking and negative shift in attitudes about how consumers feel about interfacing with his AI. he told E-Commerce Times.
Her company provides a cloud contact center platform for AI-powered customer service.
“I've definitely seen a change in attitude. There's some shocking information about how gen AI is being used to recommend products that people don't use. And shoppers… have high expectations for data security and transparency, which are not being met,” she said.
AI and Gen AI – What’s the difference?
Artificial intelligence has been quietly introduced with limited capabilities for nearly a decade. Its use cases have gradually improved in recent years thanks to advances in machine learning (ML) and its combination with robotic process automation (RPA).
Last year's release of ChatGPT brought significant progress in increasing automation of repetitive, rules-based activities while minimizing human oversight. This advancement has expanded the capabilities of AI to encompass more comprehensive capabilities.
All AI programs are not of the same species. Traditional artificial intelligence focuses on analysis and classification. Generative AI (Gen AI) is a general purpose artificial intelligence that uses complex algorithms and neural networks to simulate human creativity and generate new content from text, images, sounds, animations, 3D models, and other types of models. It is a subset of intelligent technology. data.
Gen AI captures the nuances of language and generates output based on trained patterns. Its models can remember previous interactions, resulting in a more consistent and relevant conversation experience for users.
However, generational AI cannot make decisions that involve many complex factors. At least not yet. They're great at making data-driven recommendations, but they're bad at including the all-important human factor.
Introducing AI into productive practices may not be enough
Research shows that a disconnect exists in how companies can safely and accurately integrate generational AI skills into business cycles and avoid unintended consequences. In the retail and call center industries, consumers do not agree on how AI is impacting customer experience (CX).
Flanagan has noticed a clear change in user attitudes as gen AI capabilities are integrated into the Talkdesk platform. Not all of the changes reflected in the company's numerous studies are in favor of AI.
“Some of the pre-holiday AI research was talking about how shoppers feel about AI and retailers. The vast majority of them aren't doing that,” she told E-Commerce Times. told.
Big brands like Walmart are legally using generative AI. But Flanagan says a wide range of her company's customers don't know how to take advantage of it.
“Product description copy is easy in some ways. In some places, the customer service use case is fine. But there's still a lot of hesitation,” she said.
Consumer sentiment towards AI
A recent report from Talkdesk revealed some surprising findings on the use of AI in product recommendations, revealing that the majority of individuals surveyed are not leveraging AI. Additionally, consumers highlighted unexpected demands for data security and transparency.
Flanagan emphasizes the urgent need for a strategic review to effectively engage customers and points to use cases that are currently emerging.
Still, she cautioned that there are problems with the use of AI that need to be resolved. This fix should be easy to accomplish, especially in applications where it acts as an agent assistant rather than a customer-facing integration.
“The reality now is that we do it in every customer-facing area. It should be seamless for the customer, but it's something that some parts of the back office use like marketing operations and obviously agent assistants in a self-service world.” It's a little more risky than you might think if you use it like that,'' Flanagan explained.
Examples of Talkdesk reports on how shoppers are using AI show:
- 79% of shoppers refrain from purchasing because AI-powered product recommendations aren't tailored to their interests.
- 71% never buy a recommended product because they feel like they're being watched by a brand.
- Only 28% of those surveyed believe their retailers are handling their data securely and wisely.
“This is a huge mistrust when it comes to AI,” she said. “What we have to do this year is pause for a moment and think, what is our strategy?”
Another study showing AI success
Yet another prominent AI report takes a very different view. According to a new survey from MessageGears, 99% of marketers say the use of AI has impacted their ability to understand customer preferences and behavior.
A key takeaway from our survey of enterprise marketers at companies with 500 or more employees is that the majority are already using AI in marketing and are seeing results. A big goal for marketers today is to build real connections with their customers. This increases brand awareness and builds trust.
Bottom line: Business leaders surveyed say AI is particularly helpful in improving customer engagement.
“AI algorithms are like the secret sauce for marketers to dig deep into customer data,” Will Devlin, vice president of marketing at MessageGears, told E-Commerce Times.
“Marketers can then fine-tune messages on the fly with inside information about preferences, behaviors, and demographics. , making the connection between a brand and its audience accurate and meaningful.”
Conflicting results Distortion of AI evaluation
Only 53% of marketing professionals surveyed by MessageGears said they were very successful in connecting with customers. This statistic leaves a lot of room for improvement.
Additionally, 53% would like to use this technology to more accurately identify users who are most likely to make a purchase. Half want AI to help them pinpoint the most effective channels to reach customers.
A MessageGears study found that 58% of marketers are using AI in targeted advertising campaigns. Almost half (49%) use this technology for personalized email marketing, customer support and service, and customized product recommendations.
Additionally, 97% of corporate marketing professionals using AI said they were successful in delivering personalized content and recommendations, 39% said their experience was exceptional, and 99% said their experience was exceptional. They say AI is making a big difference in understanding customer preferences and behavior.
An important application of gen AI from a marketing perspective in 2024 will be to help solve customer engagement problems. Customer engagement is about providing value and communicating that value in a way that makes customers feel connected and appreciated, Devlin says.
“Customers should be excited about what they receive from you. Messages should be timely, relevant, and delivered on the channels that matter most to the customer. Businesses already know this, but Achieving this often requires a manual guessing game,” he told E-Commerce Times.
Devlin added that marketers should anticipate the growing use of predictive AI and modeling to determine the most effective communication strategies with customers and eliminate the need for guesswork. Marketers can combine these predictive AI insights with generative AI to further refine and personalize their messages.
Growing the AI enterprise
ChatGPT's one-year anniversary marks a remarkable aspect in the rise of generative AI, marveled Priya Vijayarajendran, president and CTO of technology at Gen AI software developer ASAPP. He emphasized that its democratization and ability to bring together talent from different areas of the technology world will enable the best and brightest to leverage their skills and collaborate to “get things right.”
“Going forward, responsible data use and investment in AI privacy and assurance will be essential to unlocking the potential of generative AI for enterprise innovation. This innovation must continue. Now there is no slowing down,” she told E-Commerce Times.
Generative AI continues to deliver incremental innovations across GPU, LLM, and computing frameworks. She spoke about the progress expected this year. Data dominates as the most important differentiator, and with a hybrid focus on her domain, she applies the LLM to achieve accuracy, time to value, and scale.
“The convergence of these vectors will be the key to unlocking exponential value.” [of Gen AI] For companies,” concluded Mr. Vijayarajendran.
