AI can’t be ignored. A culture of learning is key to unlocking its value
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This time last year, we were having discussions about how much AI – and, specifically, generative AI (GenAI) – would be used in the workplace, whether it would replace humans and if it was possible for AI to be a beneficial force in the labour market. Now, AI is here. Many have turned to GenAI tools to save time and effort on administrative tasks such as writing emails, summarizing documents and synthesizing meeting notes.1
While the offloading of administrative tasks is a promising development, especially as it allows career service professionals to shift their focus to client relations and support, it only scratches the surface of the possibilities of AI.
AI offers enormous potential in career services, job coaching and other related fields, with tools already available to provide feedback on interview responses, customize resumes to job postings, understand labour market trends and plan career paths.
The new challenge is to support effective learning about AI to enable responsible and beneficial use of the technology. It’s important for leaders to embrace thinking about AI not as a static technology that you can understand, implement and master, but as a skill that needs to be refreshed constantly.
AI can’t be ignored. Organizations need to intentionally foster cultures where experimentation is encouraged but grounded in an understanding of the risks and implications.
Check out more articles in our new series – AI in Career Development: What’s New, What’s Next:
- Consent, access and more: Everyday AI ethics in career development
- AI in career development: Are career professionals ready?
- 7 AI tools for career exploration
Organizations can’t afford to miss out on AI
Whether leaders acknowledge it or not, their staff is already adopting and using AI. This is known as the “bring your own AI” approach, in which workers access free tools like ChatGPT and experiment with its potential for greater productivity, automating tasks, etc.
While experimentation can yield helpful breakthroughs, it also carries risks:
- Confidential information can be shared and compromised via AI tools if users aren’t aware of data security concerns.
- AI has inherent biases and can make errors, especially when users are new to AI and unfamiliar with prompting.
On the other hand, some workers are simply hesitant to use AI, whether out of fear of security implications or a lack of understanding of how tools work. A hands-off approach only results in a gulf within an organization, with some team members using tools to their benefit, some generating risk and some being left behind entirely.
AI, when used thoughtfully, can help a newcomer jobseeker navigate cultural norms in interviews and in the workplace or help a mid-career jobseeker identify opportunities to transition into a new industry. To seize these opportunities, however, it’s essential that we’re aware of potential biases so we can truly serve a jobseeker’s unique needs, and that we’re mindful of their security.
For career service professionals, it’s also important to remember that many of the clients you serve will transition into roles where they’ll be expected to use AI regularly. This makes it all the more essential for those working with jobseekers to understand AI’s ongoing evolution.
How to get more out of AI
In 2024, Magnet launched MagnetAI, a resource hub and webinar series to help SMEs, community organizations, educators and workers navigate AI adoption.
Our central message is that because AI is so vast and constantly evolving, the ideal approach to adoption is one in which teams understand the workings of relevant tools, identify and apply those tools to their work, and have opportunities to share what they’ve learned and ask questions in collaborative settings.
Because AI’s use cases are seemingly endless, it’s easy to become overwhelmed, distracted and discouraged by the deluge of information.
Organizations should be flexible in how they approach AI adoption, but keep in mind a few key principles:
- Build knowledge: In addition to AI’s practical applications, teams need to understand how AI functions. Take the time to understand the basics of large language models, how they work, and how to think critically about issues like bias and data security.
- Break it down: Because AI’s use cases are seemingly endless, it’s easy to become overwhelmed, distracted and discouraged by the deluge of information. Organizations should take the initiative to find simple ways that AI can add value to their work and encourage teams to try it. This openness will also help overcome psychological barriers for those still nervous about using AI. Ideally, this should be backed by investment in formal training or workshops.
- Stay in touch: Keep communication frequent and open. Whether you use an internal newsletter, regular working group meetings, or tools like Slack and Microsoft Teams, your organization needs a space to share discoveries and resources, ask questions, raise concerns and find solutions together.
These three pillars provide the foundation for what Magnet has called the marketplace of learning model – a responsive learning hub developed through the input of sectoral leaders. As we developed and rolled out MagnetAI, our goal has always been to provide organizations with a one-stop shop for trusted tools and information that meets a critical need.
We encourage organizations to use these three pillars to consider how they can establish their own internal learning hubs and to also work with others across the career services sector to create mutually beneficial opportunities for upskilling.
In contrast to a “bring your own AI” approach, these principles offer a foundation for leaders and their team members to work together and tackle AI’s growth head-on, address challenges as they arise and reap the most benefit for your organization.
Disruption or opportunity?
As conversations around AI progress, it’s important to acknowledge that it represents both disruption and opportunity. AI’s impact won’t just be limited to AI tools, but will interface with other technologies (e.g. robotics, manufacturing, data analysis, ecommerce) to trigger exponential change. These concurrent dynamics create a responsibility for us to continually understand and adapt in the coming years.
The greater our understanding of AI tools, the more opportunity we have to drive productivity and enrich the support we offer Canadians. This is why I encourage those of us in education, skills training and career counselling to treat AI as a skill we can build and deploy to add more value to the service we provide and enable our professional growth.
