Taco Technologies is dedicated to helping organizations of all shapes and sizes, from schools and law firms to libraries and small businesses, manage the systems they rely on every day.
With expertise in print enablement, document workflows, and workplace technology, they’ve been a go-to partner for teams looking to simplify how work flows across tools for decades.
In recent years, Taco expanded its offerings beyond print, shifting focus toward direct selling, helping organizations implement workplace tools like Asana and Odoo, and supporting a broader range of operational needs.
But growth brought complexity. More products and customers meant more requests and a growing volume of work managed manually through shared documents and email chains.
To help, Taco turned to AI Studio to automate routine tasks and create consistent workflows. The result? They dramatically reduced time spent on admin work, allowing the team to focus on keeping projects moving forward without the usual bottlenecks—innovation that earned them recognition as Asana's Future of Work with AI Partner (APAC) at the Partner Summit.
“To say that this is transforming our business bit by bit is an understatement.” said Charlie Masters, General Manager at Taco.
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One of Taco’s most impactful use cases started in an all-too-familiar place: someone’s inbox.
Technical account managers regularly receive complex migration requests from resellers or customers, such as shifting from on-premise print management systems to cloud-based solutions. These requests include a mix of customer details and technical specifications, followed by a simple question: What do we do next?
Previously, responding to those emails meant hours of manual research and documentation. Now, that process runs through AI Studio: with clear intake, AI-powered research, and a reusable framework for generating implementation-ready plans in minutes instead of days.
“We’ve created a technical support analyst job that [our technical account manager] used to do himself. It would take him days to do this—lots of meetings, lots of back-and-forth with questions,” said Charlie. “Now we can give this job entirely to AI Studio.”
Here's an anonymized example of that workflow showcasing a fictionalized organization and employees:
Instead of relying on ad hoc email threads to kick off migration requests, Taco uses a standardized Asana form, connected to an intake project, to collect request details. The form captures consistent fields like:
Company and requester name
Customer reference number
Number and types of multifunction devices (MFDs)
Key print environment features (e.g., mobile printing, integrated scanning)
Conditional questions that adapt based on answers
This approach ensures nothing gets missed and creates a clean data trail, making it easier for the team (and the AI) to get started.
Once the form is submitted, the task is automatically routed to the “Research” section of the intake project, where Taco’s AI Studio workflow takes over.
Here, the AI acts like a technical research and support analyst, tasked with assessing risk, surfacing key details, and drafting a migration plan based on established best practices.
To do this, the AI references a set of internal resources provided as context in the AI Studio backend, including a 25+ page migration guide, a linked implementation project with historical customer data, and clear guidance on tone, structure, and formatting.
AI evaluates the form submission against this context to determine whether it has enough information to proceed. If not, it flags the task and moves it to a “Failed Intake” section, saving the team from chasing down missing details and ensuring only ready-to-go requests move forward.
If the request passes the research check, the AI automatically generates a new task with a full migration summary. The output includes:
Key customer and reseller information, such as contact details and reference numbers
A list of potential blockers or complexities that might impact the project
A step-by-step migration plan, complete with recommended actions, timing estimates, and technical considerations
These aren’t generic to-do lists; they're multi-week implementation plans, covering everything from legal reviews and infrastructure checks to pilot testing and full deployment. Each plan is tailored to the request and grounded in internal expertise.
“What we’ve done is turned [our guidance document] into part of our workflow,” said Charlie. “So that expertise is now able to be—in minutes—put into a plan. And that is so powerful for us.”
Once the AI-generated migration plan is complete, it’s routed to a technical team member for review. Instead of drafting plans from scratch, they validate the details and sign off before implementation begins.
It’s a simple shift that makes a big difference: saving at least a day per week while maintaining the quality customers expect.
This isn’t about replacing expertise—it’s about scaling it. “You can’t just let AI do your job for you,” said Charlie. “That’s not the point. The point is that it’s such a big time saving, it’s so well integrated into your workflow, that it becomes more consistent and easier for you to do your review. Human expertise is still really important.”
With AI Studio, Taco transformed a manual, time-intensive workflow into a repeatable system that delivers accurate, quality migration plans with far less lift.
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Taco didn’t stop with technical workflows. Their CEO, Jonathan Milne, set up a virtual executive assistant using AI Studio to triage and route tasks directly from his inbox.
The system evaluates incoming tasks based on a detailed set of criteria Jonathan defined, and then automatically sends them to the right place. For example:
Invoicing requests are routed to the Accounts team
Business development leads are assigned to the appropriate member of the leadership team
Partnership opportunities and escalations are categorized and sent to stakeholders
General tasks are assigned based on their content and priority
By automating this kind of inbox triage, tasks move quickly, consistently, and without anything slipping through the cracks.
“His inbox is constant,” Charlie said. “So to get back focus and get back time by outsourcing the triaging of his inbox to a virtual executive assistant is so powerful.” The impact isn’t just operational—it’s personal.
“He’s having lunch more,” Charlie added. “That sounds silly, but we get wrapped up in the narrative that AI is going to give you time back to be a leader, to do the strategic tasks. It's just giving you a little bit more breathing space to be great. And if great means doing strategic tasks, that’s wonderful. If great means you get to consistently have lunch, that’s wonderful too.”
With early wins in place, Taco is now expanding AI Studio’s footprint across the business. The team is actively collaborating with every department to identify high-impact opportunities, whether it’s creating new triage systems, building internal workflows to support different customer needs, or helping teams manage stakeholder needs more effectively.
“We’re actively working with all teams to find more triage steps and more support steps in all our workflows,” said Charlie.
They’re also continuing to refine what they’ve already built, planning to evolve workflows over time based on real usage. Potential planned updates include adding reviewers to incomplete submissions and integrating AI plans more seamlessly into reseller processes.
As they continue to expand AI Studio across the organization, the team at Taco sees the tool not as a substitute for their knowledge, but as a way to double down on the work that matters, without doubling the effort.
“You don’t need to start with perfection to get these savings,” Charlie said. “Just get going. Understand that it’s not replacing your job. It’s helping you do it more efficiently and consistently.”
AI 스튜디오는 Starter, Advanced, Enterprise, Enterprise+ 플랜에서 사용할 수 있습니다.
Asana는 AI 원칙 에서 공유하고 AI Studio 공지 사항 에서 강조한 바와 같이, AI의 현재 한계를 극복하고 정확성을 보장하기 위해 인간 중심의 접근 방식이 AI와 함께 일하는 가장 좋은 방법의 기본이라고 굳게 믿습니다.
AI는 매우 강력하지만 완벽하지는 않습니다. 인간이 AI의 작업을 검토하는 것은 단순히 실수를 포착하는 것이 아니라 모든 것이 계획대로 진행 중인지 확인하는 것입니다. 팀은 처음부터 모든 것을 수행하는 대신 AI가 생성한 내용을 빠르게 검토하고 구체화할 수 있습니다. 이를 통해 더 많은 프로젝트를 처리하고, 더 많은 데이터를 분석하고, 혼자서 할 수 있는 것보다 더 많은 업무를 수행할 수 있습니다.