Artificial intelligence is no longer a futuristic fantasy, it’s an increasingly pervasive reality shaping how businesses interact with their customers. However, the integration of AI into service delivery isn’t a one-size-fits-all solution. Generational differences in perception, expectation, and comfort levels with AI necessitate a nuanced approach to ensure effective and satisfying customer experiences.
Generational perceptions of artificial intelligence are multifaceted, influenced by a lifetime of technological evolution and societal discourse. Anthony Brown, director of solution consulting, NICE CXone Mpower, comments, “Older generations, such as the Baby Boomers, tend to approach AI with caution, perceiving it as a potential threat to jobs and privacy. Generation X tends towards a more balanced view, seeing AI as a useful tool that can streamline operations and drive efficiency. The younger, digital-native generations often integrate AI naturally into personal and professional settings, seeing it more as a convenience”.
However, these broad generalisations are increasingly challenged by the rapid pace of technological change and significant global events. “The COVID-19 pandemic, for instance, catalysed a dramatic acceleration of digital adoption across all age groups. Many older consumers, previously hesitant about online interactions, rapidly adapted to digital platforms for communication, shopping, and accessing services. This newfound digital fluency is beginning to influence their engagement with AI as well”, says Brown.
How different generations perceive and engage with AI
The key differentiator in how individuals perceive AI often lies not solely in their birth year but in their current life context. Factors such as employment status, the nature of their profession, and the extent to which they directly interact with AI in their daily lives play a significant role in shaping their views.
Brown says, “Each generation brings distinct communication preferences and expectations when engaging with AI-powered services. Companies might find that younger consumers often favour casual, conversational interactions, particularly when dealing with chatbots. However, this relaxed tone can alienate older users who may prefer more formal, straightforward exchanges that reflect traditional customer service norms”.
Despite generational differences, consumers universally expect AI to mirror their intent, language, and communication style. According to Brown, the most effective AI experiences are those that adapt to the individual, offering a frictionless option to escalate to a human agent when needed, responding in a tone that matches the user, and being available through the customer’s preferred channel or device. Service must be flexible and intuitive, not rigidly tied to generational assumptions.
The common thread uniting all generations is the importance of relevance and utility. Regardless of age, individuals are more likely to embrace AI when it demonstrably improves their lives or solves a specific problem effectively.
Universal expectations that transcend generations
Despite these generational nuances in communication style, there are universal expectations that transcend age. All consumers, regardless of their generation, expect AI to understand their intent accurately, process their language effectively, and adapt to their individual communication preferences.
Brown highlights, “The most effective AI experiences are those that adapt to the individual, offering a frictionless option to escalate to a human agent when needed, responding in a tone that matches the user, and being available through the customer’s preferred channel or device. Service must be flexible and intuitive, not rigidly tied to generational assumptions”.
Flexibility and user-centricity are key; service design should avoid rigid adherence to generational stereotypes and instead focus on creating adaptable AI that caters to individual needs and preferences.
Past experiences shape future perceptions
Comfort levels with various AI applications also differ across generations, largely influenced by prior experiences and exposure. Older consumers may harbor lingering frustrations from earlier, less sophisticated attempts at AI, such as voice assistants that struggled with accents or frequently misinterpreted commands. These negative past experiences can create a sense of wariness towards conversational AI, even as the technology has significantly improved.
Younger generations, on the other hand, generally exhibit higher levels of comfort with a wide range of AI applications[i]. They readily utilise AI-driven personalised recommendations for entertainment and shopping, and they engage with chat interfaces as a routine part of their online interactions.
Interestingly, the current capabilities of AI often outpace widespread user adoption across all demographics. “The next 12-18 months are likely to see significant improvements in usability and reliability, especially in speech-based AI and chatbots. Consumer confidence across all generations will grow accordingly as trust is rebuilt through better experiences”, says Brown.
As these improvements materialise and consumers experience more seamless and effective AI interactions, confidence and comfort levels across all generations are likely to increase, gradually rebuilding trust that may have been eroded by earlier technological limitations.
Self-service
When it comes to preferred use cases for AI in service, self-service emerges as a universally accepted and economically attractive application. “Self-service remains one of the most widely accepted and financially compelling use cases for AI. Organisations often prioritise containment to reduce reliance on costly human resources, though this must be balanced with customer satisfaction. AI’s ability to deflect basic queries only works when it still delivers a high-quality experience, regardless of age or channel”, says Brown.
Businesses often prioritise AI-powered self-service to reduce their reliance on human agents and contain operational costs. However, the success of this strategy hinges on maintaining a high-quality customer experience, regardless of the user’s age or preferred communication channel. AI’s ability to effectively deflect basic inquiries is only valuable if it provides accurate, timely, and satisfactory resolutions.
AI as coworker or assistant
A compelling emerging use case for AI that resonates across generations is its role as a digital coworker or assistant. AI’s role in the workplace is multifaceted. It can automate repetitive and mundane tasks, freeing up human employees to focus on more creative, strategic, and complex responsibilities.
Think of AI handling data entry, scheduling meetings, or sifting through large datasets to identify key insights. This not only boosts productivity and efficiency but also reduces the likelihood of human error, leading to more accurate and consistent outcomes. Brown observes, “AI augments the user’s capability by suggesting relevant knowledge articles, supporting notetaking, and navigating complex internal systems, rather than replacing the worker. This application is particularly effective in customer service environments, as it helps agents stay focused on human interactions while offloading routine tasks to AI. The result is improved employee productivity and better customer outcomes”.
Furthermore, AI can act as a powerful assistant in decision-making. By analysing vast amounts of data at incredible speeds, AI can provide valuable insights and predictions that help inform strategic choices. This data-driven approach can lead to more effective problem-solving and the identification of new opportunities that might be missed through human analysis alone.
Privacy and ethics
Generational values significantly shape perceptions of AI ethics and privacy. It’s a common assumption that younger users are more nonchalant about data sharing due to their lifelong exposure to digital platforms. Their willingness to share information is often driven by a desire for connectivity and the perceived utility of new digital tools, prioritizing access and functionality. However, this perspective can be nuanced and is also influenced by individual experiences and levels of digital literacy.
In the professional sphere, privacy concerns are increasingly influencing decisions. “In the workplace, privacy concerns are increasingly reflected in procurement cycles. Detailed questions about a vendor’s AI practices are becoming standard. These cover not just how the business uses AI or train models with data, but also how individual employees use it in their daily tasks. However, consumers are more likely to accept data use, regardless of their age, when there is a clear and demonstrable benefit”.
Transparency regarding data collection and usage, the provision of mutual value, and clear communication about where data is stored and processed are crucial for building trust, whether the data is used for internal business operations or for training public AI models.
Catering to diverse needs
To effectively cater to the diverse needs of different generations, businesses must move beyond simplistic demographic assumptions and embrace a design philosophy centered on flexibility and personalisation in their AI-powered services.
“Practical steps include refining FAQ and help pages for discoverability and optimising content for natural language search, whether it’s via a website or an AI-generated search result. AI must reflect how people actually ask questions, not how businesses frame them. This improves customer satisfaction across the board when executed correctly by making it easier to access information and resolve queries quickly, regardless of age or technical literacy”.
Emerging trends
Emerging trends in AI and generational service preferences point towards a deeper integration of AI into operational decision-making, extending beyond customer-facing applications. “Contact centres are benefitting from tools like digital assistants and copilots, which are becoming increasingly valuable for supervisors and business leaders by offering proactive summaries and insights on contact centre performance. This shifts AI from a reactive support tool to a strategic enabler”, says Brown.
He adds, “A growing focus on the observability and auditability of AI is shaping future service models at the same time. Businesses are under pressure to keep AI accurate, ethical, and accountable, especially as consumers continue to scrutinise whether they can trust what AI tells them.
These trends, coupled with the inherent generational differences in digital maturity and technological comfort, necessitate a balanced approach to AI innovation. This approach must prioritise advancing AI capabilities while simultaneously maintaining transparency, ensuring ethical practices, and empowering users with control over their service experiences. Ultimately, understanding and responding to the nuanced perspectives of different generations will be paramount for businesses seeking to harness the transformative power of AI to deliver truly exceptional service.
[i] https://youthinsight.com.au/wp-content/uploads/2023/06/YouthInsightxStudentEdge_GenZ-on-AI_21.06.23.pdf