Insights and key takeaways from Asana's Work Innovation Tour Sydney 2026

What we saw (and why it matters)

This year, Apparatus Quo was represented by Josh Licence and Arsh Kaur, joined by Allison Stewart. As our new Asana consultant, this was Allison’s first event with AQ and she brought a fresh perspective to the discussions. 

Her takeaway from the summit captured the energy in the room:

“Inspiring to see the future with AI and how we can utilise AI Teammates to reduce repetitive or basic tasks, leaving space for thinking, strategy, and connection. So much to learn!”

That thread ”AI freeing humans for higher-value work, not replacing them” ran through every session. But the presentations went further than aspiration. They offered practical frameworks for how to make it happen.

The problem: AI that works alone isn't enough 

One of the most striking moments came early in the keynote, with a simple slide: "AI is not collaborative."

Most AI agents today optimise for personal productivity. They help individuals draft emails faster, summarise documents, and generate content. But they lack three things that matter when AI operates inside a team: context, checkpoints, and controls.

The result? Smart agents, but disconnected teams.

This framing landed hard because it mirrors what we see with our clients every day. Organisations aren't short on AI tools. They're short on AI that works within their team's workflow with visibility, accountability, and the ability to learn from feedback.

Asana’s solution: AI Teammates

Asana used the summit to launch AI Teammates. AI agents that don't just assist individuals, but operate as members of a team's workflow. The difference is structural: AI Teammates work through a loop of request, plan, feedback, and iterate, with human checkpoints built in at every stage.

It's a meaningful shift. Rather than bolting AI onto the edges of how work happens, AI Teammates are embedded in the system where work is already being managed. That means they inherit the context of the project, the team's priorities, and the governance structures already in place.

For organisations already using Asana as their operating system for work, this opens up a practical path to scaling AI without the usual risks of disconnected tools and ungoverned automation.

Humans + AI: Ross Dawson’s frameworks

Futurist Ross Dawson presented the “Humans + AI: Macro Workflow Roles” framework, outlining which tasks humans lead versus AI:

Human-led roles:

• Framing (setting objectives, context, standards)
• Assessment (judgment, quality control)
• Curation (choosing the best outputs)
• Synthesis (connecting insights into strategy)
• Networks (building relationships)
• Engagement (communicating with empathy)
• Feedback (coaching, reviewing, improving)

AI-led roles:

• Generation (writing, code, visuals)
• Ideation (options, scenarios, recommendations)
• Challenges (critiques, alternative perspectives)
• Analysis (categorisation, evaluation, forecasting)
• Adaptation (contextualising outputs)
• Information (retrieval, organisation)
• Refinement (iteration, improvement, clarification)

What makes this framework powerful is its practicality. It gives leaders a concrete way to evaluate every activity in their operations and ask: should a human be doing this, or should AI?

Protecting what humans do best: The EPOCH framework

Derived from MIT research by Lolaza and Rigobon, the EPOCH framework defines the areas where humans excel:

• Empathy and Emotional Intelligence
• Presence, Networking, and Connectedness
• Opinion, Judgment, and Ethics
• Creativity and Imagination
• Hope, Vision, and Leadership

This isn't about limiting AI. It's about being intentional in protecting the work that humans do uniquely well, the work that builds trust, shapes culture, and drives the kind of decisions AI can support but shouldn't make alone.

For leaders evaluating where AI fits in their organisation, EPOCH provides a useful filter: if an activity falls squarely in one of these domains, it's not a candidate for automation. It's a candidate for amplification.

The research backs it up: Team + AI beats Individual + AI 

Harvard Business School research (Dell’Acqua et al., “The Cybernetic Teammate”) shows that teams using AI outperform individuals using AI in solution quality, top-tier outcomes, and even team morale.

The takeaway is clear: AI should be a team capability, not a personal productivity tool. Organisations getting the best results embed AI into collaborative workflows, with humans actively in the loop.

Building an AI roadmap: From framing to scaling

Dawson outlined a practical four-phase AI roadmap, aligned with how AQ approaches client engagements:

1. Framing - Evaluate readiness, align AI to strategy, define governance, identify priorities
2. Planning - Build foundations, address skill gaps, establish literacy, select use cases
3. Implementing - Run pilots, define metrics, create Centres of Excellence, standardise approaches
4. Scaling - Expand AI portfolios, redesign workflows, embed in decision-making, accelerate adoption

The success factors? A Humans + AI mindset, executive leadership, AI literacy and education, and clear communication. None of these are technology problems, they're strategy and alignment problems. And that's exactly where we focus.

AQ on the Asana stage

We were proud to see Apparatus Quo featured alongside AWS and TACO on the Asana stage as a recommended partner for organisations navigating this shift. It's recognition of the work our team led by our head of services, Von Fehily has been doing across APAC to help organisations move from ad-hoc AI experimentation to structured, sustainable adoption.

It also reinforced something we believe deeply: the future of AI in organisations isn't about picking the right tool. It's about designing the right system, one where humans and AI each do what they do best, with the workflows and governance to make it sustainable.

What this means for your organisation 

If you're a leader thinking about where AI fits, here are three questions worth asking:

1. Where is your team spending time on work AI could handle? Start with generation, analysis, and information tasks, the low-hanging fruit for collaborative AI.

2. Where are your EPOCH activities? Identify the work that requires empathy, judgment, creativity, leadership and protect it. That's where your people add the most value.

3. Is your AI strategy designed for teams, or just individuals? The research is clear: Team + AI outperforms Individual + AI. If your AI tools aren't embedded in your team's workflow, you're leaving value on the table.

At Apparatus Quo, we help organisations answer these questions and build the workflows, governance, and capability to act on the answers. If the summit made one thing clear, it's that the future of work isn't about choosing between humans and AI. It's about designing the partnership well.

 Apparatus Quo is an Asana partner specialising in strategy, alignment, and scale for mid-size to enterprise organisations across APAC. To learn more about how we help teams navigate AI adoption, get in touch.