By Samantha Walravens
After a decade building AI products at companies like Spotify and Netflix, Kene Anoliefo noticed something stark about the user research process: it was painfully slow. “It usually takes 4+ weeks to complete a customer research study,” she explains. Today, as Founder of the AI company HEARD, she’s transformed that timeline dramatically: “HEARD speeds it up to just 1-2 days.”
This dramatic efficiency gain isn’t about replacing researchers – it’s about transformation. Much like how the introduction of spreadsheet software transformed accountants into financial analysts, AI handles time-consuming tasks like drafting research questions, moderating interviews, and synthesizing data, freeing researchers to focus on strategic insights and deeper analysis.
Companies like Spotify, Miro, and Character.AI are already seeing the benefits, using HEARD to collect product feedback, test new feature ideas, and build customer personas in a fraction of the time it would have taken them before AI.
Speaking to the power that GenAI holds to transform the future of work, Anoliefo admits that a big change is imminent:
“There’s definitely going to be tumult in the coming 3-5 years, but chaos is a ladder. Those who embrace AI will see themselves become eligible to do jobs that they would have been disqualified for in the past.”
For example, skills that would have taken years to master in the past— like writing, designing, and coding— can now be learned in an instant.
“Using AI tools, a user researcher could actually also be a designer, engineer, marketer and product manager — roles that have a bigger impact and voice than their current job,” Anoliefo explains.
Her observation points to a fundamental truth about technological transformation: those who adapt can find new opportunities, even as traditional roles evolve or disappear.
Which Jobs Are at Risk?
Still, the concern about AI eliminating jobs is real. In the near term, the jobs most at risk are those that involve repetitive tasks or synthesizing information from a rote knowledge base, says Anoliefo.
“Jobs that center around these tasks, like customer service representatives, paralegals and low-level writing for online content creation, are most at risk in this category,” she explains. “
Jobs that involve a low level of interpersonal collaboration are also vulnerable.
“This includes jobs where there isn’t a need for two people to work together to create, negotiate or problem solve with each other,” she says. “With these, a company could easily switch to AI with minimal disruption to the organizational culture or structure.”
While the fear of job displacement is real, Anoliefo says we need to embrace the changing landscape and provide people with training and resources needed to adapt rather than attempt to resist AI tools altogether.
After all, this isn’t the first time that we have seen technological change causing a major disruption in the workforce. When the Industrial Revolution introduced power looms, it initially displaced traditional weavers. However, the textile industry ultimately grew dramatically, creating new roles like machine operators, mechanics, and factory managers. While individual weavers faced real hardship, the transformation created more jobs than it eliminated.
AI: Great Equalizer or Source of Inequality?
Today’s AI revolution may follow a similar pattern, but at a much faster pace. And this time, the transformation will extend far beyond tech companies.
Lauren Irving, Learning and Development Specialist at insurance company Zinnia, sees AI revolutionizing the human resources field, including employee training and onboarding.
AI can create highly customized training programs tailored to each employee’s needs. Its algorithms can analyze an employee’s past performance, preferences, and goals to create unique learning paths. AI-powered chatbots offer round-the-clock support to employees, answering questions, providing clarification on course content, and offering real-time feedback.
As such, Irving says that AI has the power to be “a great equalizer, making work more accessible and empowering for everyone.” But to do this, companies must make an “intentional investment in people at all levels of the organization,” and she fears that this is not happening in most organizations.
“Without proper training on AI,” she says, “the potential for misuse or missed opportunities grows.”
This is especially significant when you consider the ethical implications of AI and its integration in the workforce, specifically the tendency of AI systems to reinforce and magnify existing societal prejudices and inequalities.
“Since AI often mirrors the data it is trained on, there’s a risk of perpetuating or even amplifying existing inequalities, which could disproportionately affect marginalized groups,” Irving explains.
Anoliefo is particularly concerned about the equity gap in AI, explaining that AI will change jobs much faster than past technologies like the Internet or PCs because of what she calls “exponential transformation”:
“With GenAI, improvements will compound because models will have the ability to recursively improve themselves over time. Humans as a whole will struggle to keep up, especially those in low-income or rural communities who already have less access to technology.”
Teaching workers new skills will require close collaboration between the public and private sectors, yet Anofielo fears that neither the government nor universities are ready to pitch in.
“Government isn’t ready to protect workers affected by these changes because regulation is slow,” she states. “Schools and universities can’t teach new skills fast enough because many teachers aren’t working directly with the latest technology.”
Adaptation is Key
Both Anoliefo and Irving agree that success lies in adaptation rather than resistance.
As Anoliefo puts it, those who embrace AI can expand their capabilities and take on roles they never thought possible. The key is to focus not on which jobs AI might eliminate, but on how to evolve alongside it.
Irving agrees, stating that “AI is not coming for your job—it’s coming to transform it.”
“Now is the time to embrace AI as a partner in your role, using it to enhance your value, expand your capabilities, and future-proof your career,” Irving explains. “By learning how to integrate AI tools effectively, you position yourself as someone who adapts to change and leverages technology to drive results. The future of work isn’t about competing with AI—it’s about collaborating with it.”
Both employers and educators will need to play a critical role in preparing individuals for the future of work.
“Employers must prioritize upskilling and reskilling programs to help employees adapt to the rapid changes brought by AI and other emerging technologie,” says Irving “Educators, meanwhile, need to rethink traditional learning models, focusing on teaching adaptability, digital literacy, and critical thinking.”
Cautious Optimism
The AI genie is out of the bottle, and it’s not going back in any time soon. So, we have no choice but to learn and adapt to life with our new genie friend.
Anoliefo is cautiously optimistic about the opportunities that GenAI will create:
“By teaching us new languages and allowing us to communicate more fluently with each other, AI will open up the door to work internationally across borders. By allowing us to design and code, AI will open the door for any creative person to build and launch products from their own living room.”
“There will be a whole new economy created by AI, one that looks different from today,” she explains. Yet she tempers her optimism with caution:
“We have the potential to shape what that (future) looks like if we are clear-eyed about the risks, aggressive in how we train and learn new skills, and curious about what we can gain from AI rather than fearful of what we might lose.”
5 Key Takeaways
- The future of work isn’t about competing with AI – it’s about collaboration and adaptation.
- AI isn’t replacing jobs wholesale – it’s transforming them by handling routine tasks and enabling workers to focus on higher-value activities.
- The speed of AI transformation means traditional education and training methods must evolve.
- Success requires both individual adaptation and organizational investment in training.
- Addressing equity issues, particularly around gender, race and access to technology, is crucial for balanced AI adoption.