Rethinking Digital Productivity in the Age of AI

This blog is based on insights shared during a recent Digital Learning Institute webinar with expert Maren Deepwell.

Productivity has always been a cornerstone of professional success, but the definition of productivity is shifting rapidly. Where once it meant simply doing more in less time, today it is about working smarter, integrating technology, collaboration, and critical thinking to achieve meaningful results.

Artificial Intelligence (AI) is accelerating this shift. By automating routine tasks, AI tools free up space for creativity, strategic thinking, and innovation. Yet, they also challenge us to rethink what counts as valuable work. As digital professionals and learning leaders, the key is not just adopting new technologies but developing the skills and mindset to harness them effectively.

AI’s impact goes far beyond efficiency. Tools such as generative AI, intelligent scheduling assistants, and adaptive learning systems are fundamentally altering workflows. This raises essential questions for organizations and individuals alike:

• What tasks should be automated versus kept human-led?

• How do we balance speed with quality in AI-supported work?

• What new skills will learners and employees need to thrive?

The answers lie in developing digital leadership, the ability to guide teams, make informed decisions, and cultivate resilience in an environment where technology is constantly evolving.

Traditional approaches to productivity often revolved around time management techniques, like prioritization or “working faster.” In the AI era, the focus must shift to value creation. Rather than asking, How quickly can I complete this task? we should ask, Does this task contribute to my long-term goals or my organization’s mission?

This means:

• Redefining priorities: AI can handle repetitive work, leaving humans to focus on strategy, empathy, and problem-solving.

• Building adaptability: As tools evolve, professionals need the confidence to learn, unlearn, and relearn.

• Emphasizing outcomes over outputs: Success is not measured in hours logged but in impact delivered.

For those working in digital learning and education, this transition presents both opportunities and responsibilities. Some actionable steps include:

• Experiment with AI tools – Try out platforms that streamline research, content creation, or learner engagement. Treat them as partners, not replacements.

• Develop critical AI literacy – Understand how AI works, its limitations, and its ethical implications, so you can use it responsibly.

• Embed productivity in learning design – Equip learners with strategies to leverage technology effectively, not just passively consume it.

• Lead by example – Demonstrate curiosity, adaptability, and reflective practice in your own work, modelling the mindset needed for the future.

Digital productivity in the age of AI is not about doing more with less. It’s about doing better, aligning our work with what truly matters, and empowering both individuals and organizations to reach their full potential.

At the Digital Learning Institute, we remain committed to exploring these themes and equipping our community with the knowledge, tools, and support they need to thrive.