Expectations vs. reality: GenAI in the workplace


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Gone are the days of manually organizing schedules, painstakingly compiling performance metrics and developing sales strategies from scratch. Now, there’s an AI for that.

The transformative benefits of generative artificial intelligence (GenAI) in the workplace is undeniable, with seemingly limitless use cases enterprise-wide.

The excitement around GenAI makes it tempting for companies to enthusiastically go all in on the technology, but pausing to plot out your GenAI path is crucial – especially when it comes to security, ethics and governance considerations. Meeting and exceeding GenAI expectations demands careful, measured implementation, deep-seated expertise and understanding both the possibilities and limitations of the technology.

Otherwise, the promise of GenAI might come across as more myth than reality.

To maximize the capabilities of this technology in a responsible way, brands first need a strong foundation to build their GenAI toolkit. That means lining up technologies, infrastructure and expertise to ensure smooth, successful integrations. Here are some reality checks to consider when evaluating GenAI for your workplace.

Automation vs. augmentation

Expectation: GenAI will fully automate complex tasks, leading to significant reductions in workforce requirements.

The fear of AI replacing humans at work is palpable. According to Washington State University’s 2024 AI and Business Readiness survey, 32% of 1,200 professionals polled said they are concerned that AI adoption may make some employees’ jobs obsolete.

We often think of individuals who perform specific and “easy to automate” tasks such as data input and processing as the most vulnerable to AI-related job loss. However, since GenAI is able to create novel and original content, it has been predicted to undertake tasks in fields like legal research, journalism and data analysis.

Reality: No AI is a set-it-and-forget-it technology; rather, all AI needs continuous human oversight to operate accurately and efficiently. It’s better at augmenting human capabilities than replacing them outright.

While some roles have changed as GenAI becomes more integrated, the technology has shown that it can enhance productivity, help employees develop new skill sets and enable brands to set new standards in customer care.

In a customer support setting, GenAI can radically enhance the customer experience (CX) with its ability to quickly analyze and summarize large volumes of data to make specific recommendations, helping agents to deliver prompt service. Using GenAI to gather data and suggest possible solutions allows agents to focus on strategic decision-making and driving customer satisfaction through more personalized and empathetic interactions.

Insights: Fully capitalizing on GenAI demands thoughtful resource allocation across a company. Adoption of GenAI can fail when it’s not paired with seamless tech stack integration and the right resources and expertise, including robust human oversight and dedicated AI-focused teams. Offering employees continuous learning and development opportunities is also paramount to ensure they have the ability to build internal capacity, facilitate job mobility and discover new ways of collaborating with AI, thereby cultivating a workforce that’s adept at navigating the evolving technological landscape.

Standalone solution vs. integrated tech stack

Expectation: Companies can adopt GenAI platforms as a standalone solution that requires little integration into existing legacy systems in order to reap immediate benefits like productivity and efficiency gains.

Reality: GenAI is a lot of things, but it is not just plug-and-play. Companies must invest time and resources into getting an algorithm ready for implementation, as well as continuous monitoring and testing to ensure it’s functioning as expected. Just as a new human employee requires a comprehensive onboarding and training to ensure their skills are up to date, GenAI also needs proper integration into a company’s existing tech stack and continuous fine-tuning to ensure optimal performance.

These kinds of complexities can make business leaders feel overwhelmed. A survey of 2,000 global executives by Boston Consulting Group found that more than half (52%) of respondents said they don’t fully understand GenAI and actively discourage its use across their organization. As the saying goes, we often fear what we don’t understand, but inertia on GenAI adoption isn’t the answer.

Insights: To succeed, brands must be prepared to address several critical factors during GenAI implementation. Thoughtful integration with legacy systems is crucial in addition to establishing a robust process and governance structure for continuous training and monitoring to ensure the outputs are as accurate as possible.

Predictable, accurate outcomes vs. unforeseen consequences

Expectation: GenAI can consistently generate accurate and high-quality outputs in creative and decision-making contexts.

Reality: GenAI is a powerful tool, but its propensity for serving up misinformation is well-documented. CNET recently issued corrections on 41 of 77 articles written by AI. The inaccuracies, which range from wrongly explaining basic financial terms to outright plagiarism, are also known as hallucinations. These hallucinations are especially worrisome because they often sound plausible, but are missing necessary context.

Insights: In the age of GenAI, good data and stringent data governance practices have to go hand-in-hand. Good data comes from sourcing and optimizing large, diverse and high-quality datasets. Good governance comes from developing mechanisms to protect the integrity and privacy of data while also keeping humans-in- the-loop to mitigate hallucinations and ensure all AI output meets organizations’ standards. In a global context, that also means monitoring evolving regulations and ensuring compliance with policies like the EU’s General Data Protection Regulation and the California Consumer Privacy Act.

Together, matching good data with good data governance helps protect companies and consumers, builds trust between them and a foundation for sustainable business growth.

Delivering on GenAI’s promise

To be at the forefront of responsible GenAI adoption, brands need a balanced and informed approach. That means strategic planning, continuous learning and good governance.

To that end, a survey by Everest Group and supported by TELUS International found 76% of businesses are considering outsourcing their GenAI development to third-party providers to help manage and mitigate data security and privacy, exposure risks and regulatory compliance. Business leaders should choose a partner that prioritizes privacy by design principles, notably ones that have earned their ISO 31700-1 certification. Partners with this international certification are more likely to ingrain privacy principles into all facets of their work, from business operations to building a culture where employees are engaged in maintaining stringent standards.

All that preparation strategically positions businesses to confidently move forward on the realities of GenAI without falling into a chasm of unmet expectations.

Michael Ringman
Michael Ringman is the Chief Information Officer at TELUS International and has been with the company since 2012. As CIO, Michael remains focused on driving continuous innovation for both customers and team members, and has built his career on implementing technology services, especially developing public and private cloud solutions for retail, government, technology and finance verticals. Michael holds a Bachelor of Science degree in Aerospace Engineering and a Master of Science in Telecommunications, both from the University of Colorado.


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