DMC Strategy 2026: Why FIT Revenue Growth Is Harder Than It Should Be
A practical examination of pre-booking productivity, conversion, and the role of AI copilots in modern DMC operations
The rarely addressed growth ceiling
For many Destination Management Companies, the FIT (Free Independent Traveller) segment represents both the greatest opportunity and the greatest operational strain.
Industry research suggests that FIT travel is expected to outpace organised group growth through 2026, driven by traveller preference for personalisation, flexibility, and unique experiences rather than fixed itineraries. Phocuswright research notes that independent travel continues to gain share as travellers increasingly expect bespoke planning supported by digital tools rather than standard packages.
Yet despite this demand, many DMCs find that FIT revenue growth is constrained — not by sales capability or destination knowledge, but by finite systems, finite teams, and increasingly complex pre-booking workflows.
TourConnect AI has been working with DMCs globally for 10+ years, supporting their strategic objectives with market leading travel technology. This whitepaper explores a simple but uncomfortable question that we’re often asked:
Why do capable DMCs, with strong demand and experienced teams, still struggle to scale FIT revenue as much as they believe they should?
The answer is rarely commercial. More often, it sits quietly in the pre-booking process — in how quote requests are handled, itineraries are assembled, and consultants move between disconnected systems under time pressure. These operational challenges typically require more courage and care to implement, which even in 2025 remains the domain of tech savvy decision makers.
How much of your pre-booking flow is still manual?
Most DMC teams underestimate how much manual effort still exists in their pre-booking workflow. Perhaps it is comfortable and human nature to do so. However, we are now firmly in the era of AI powered solutions.
Many industries including finance, accounting and law are already deeply buying into AI powered solutions and seeing widespread success. This is no longer the preserve of ‘early adopters’. Your competitors may already be months into a quiet pilot programme to test AI enabled operations to remove most of the manual steps.
Even with modern DMC reservation systems or well-honed proprietary systems in place, large portions of booking admin and itinerary creation remain human-driven:
Interpreting free-text agent emails
Extracting services from PDFs, spreadsheets, or links
Re-entering data into booking systems (Context switching as they go)
Building first-draft itineraries from scratch
Checking rates, seasons, and availability line by line
Across Australia, reflecting on 12 months of using an AI Copilot, described the reality candidly:
“Before we implemented an AI Copilot, our consultants wasted hours every day simply data entering services, manually assembling bookings and quotes using the content of our agent emails.” - Kathy Turner, General Manager, Across Australia
This time is consumed before consultants have the opportunity to apply judgement, creativity, or supplier insight — the elements that actually differentiate a FIT itinerary.
What is the hidden cost of switching between systems?
Most DMC teams operate across multiple tools: email, attachments, booking systems, supplier portals, spreadsheets, and internal notes.
The productivity cost of context switching is often invisible — but significant.
A Harvard Business Review study found that employees lose an average of 9% of their working time simply refocusing after switching between applications.
All DMCs know that FIT travellers are demanding more speed and clarity. Context switching is the enemy of this, with human errors ramping up each time a consultant switches window from Outlook to the Availability List to the Profit Calculator.
You may have 50+ micro steps in your pre booking flow. Each one acting like a death by a thousand cuts. If a DMC wants to improve personalisation of every itinerary, then increasing the cognitive space consultants have everyday to design thoughtful itineraries should be part of 2026 strategy.
How often are consultants blocked by rate and availability issues?
Expired rates, missing services, and partial availability are not edge cases. They are part of daily DMC operations.
The real issue is when these problems surface.
When consultants only discover availability or pricing issues late — after manually assembling an itinerary — the opportunity cost is high. Files must be reworked under pressure, responses are delayed, and confidence can erode on both sides.
Across Australia noted that before automation:
“On busier days, it was not unusual for travel consultants to still be entering new requests into our system towards the end of the working day.”
Earlier visibility into services and structure changes this dynamic, allowing teams to engage suppliers sooner and respond with greater confidence.
What are the “unknown” manual tasks eroding productivity?
Some of the biggest productivity drains in FIT quoting are not obvious.
They include:
Rebuilding similar itineraries repeatedly
Re-entering services that differ only slightly
Manually applying implicit supplier preferences
Losing partial work when switching tasks mid-flow
Pacific Destinations NZ, nearly 18 months after they first used Itinerary Assist AI, observed the effect of removing these hidden tasks:
“Itinerary Assist AI has reduced the time spent on repetitive administrative work, allowing our team to focus more on tailoring itineraries and responding faster to agents.”
Individually, these tasks feel manageable. Collectively, they absorb the majority of time allocated to FIT quoting.
What does productivity look like when an AI Copilot works alongside the team?
When AI is introduced as a copilot, rather than a replacement, the nature of work changes.
Instead of starting from a blank page, consultants begin with:
A structured first-draft itinerary
Services already extracted and positioned
Rates and availability applied where possible
A clear base to refine, personalise, and improve
This result will vary significantly based on the DMC staff, the quality of the DMCs data and the maturity of the AI software solution itself. As Tourvest’s CIO described it:
“In automating complex, unstructured itinerary requests, TourConnect AI frees top talent to focus on ever scarcer human-to-human moments that build loyalty and delight customers.” — Dieter Holle, CIO, Tourvest
The key benefit of a well implemented AI Copilot for DMC operations is more creativity from consultants and much faster response times. In other words, better customer service and better quality work. There is certainly room for caution and the decision must be taken carefully. However, done right, AI Copilots have the ability to turn DMC staff into the Superman and Superwoman of itinerary building.
Can AI really do what you want it to do?
This is the question most experienced DMC leaders ask — quietly and reasonably.
The short answer is yes, but with an important distinction:
Not all AI is built for DMC operations.
Generic AI tools are impressive at creating theoretical itineraries but they’re not based on your pricing or availability. Your DMC may be a very successful business but in the context of every business segment that uses ChatGPT or Perplexity, there is almost zero probability that they will enable a solution that is designed for DMC workflows and your specific tech stack in a hurry. It is a problem most suitable to travel AI specialists — deeply tied to booking systems, service logic, rate structures, DMC preferences, and regional nuance.
Purpose-built AI understands:
How DMCs structure itineraries
How Tourplan and similar systems organise services
How rates, seasons, and preferences interact
Where human review is essential
A focused travel ai tool like Itinerary Assist AI can solely focus on first-draft itinerary quality. Over time, the service line accuracy has increased to 92% on average across active Itinerary Assist AI clients, meaning that services suggested by AI make it into final itineraries sent to the client 92% of the time.
AC Group UK described the impact this way:
“AI itineraries have been a game changer for us. The system keeps learning, and the more we use it, the more reliable and useful it becomes for our consultants.” Rob Russell, AC Group UK
This ability to improve over time is what allows teams to trust AI outputs — and trust is essential for sustained productivity gains.
How long does it take to see meaningful results?
One of the quieter concerns among DMC leaders is implementation risk:
Disruption to booking systems
Staff resistance
Projects that promise transformation but stall
The most successful AI implementations observed share three traits:
They integrate around existing systems
They allow side-by-side comparison with current workflows
They start with small, controlled rollout teams
Across Australia followed this approach, running AI alongside existing processes before scaling. As a result:
“Service requests are sent to suppliers far quicker than before… responses are generally quicker simply because they have our booking requests so much earlier in the day.”
Right now, AI is the most hyped technology there is. Separating signal from noise is incredibly difficult for DMC decision maker. All we can suggest is that you should implement with a strong core team so that the rollout has the highest chance of buy-in and success. These are commonalities for any technology roll-out, but they hold true for our foundation Itinerary Assist AI clients.
The amount of time required to see strong benefits will vary based on your tech stack and implementation team. It could be anytime between 3 weeks and 3 months, with continued benefits building throughout the first 12 months.
What separates average and excellent FIT performance?
The distinction rarely lies in supplier access or destination expertise.
It lies in:
How quickly first drafts are delivered
How much time is spent refining rather than assembling
How confidently teams respond to incomplete requests
How consistent quality remains under pressure
AI does not create excellence on its own. But when it removes repetitive work, it allows experienced consultants to apply judgement where it matters most.
Conclusion: growth is possible, but it requires clear-eyed assessment
Most DMCs already have the demand, expertise, and market position to grow FIT revenue further. What holds DMC’s back from growth in the FIT segment is operational process friction, accumulated over years and quietly accepted as unavoidable.
This paper does not argue for change for its own sake. It argues for a stoic, clear minded assessment of the pre-booking workflow:
Mapping out where time is lost before value is added
Where systems fragment attention
Understanding if your data quality is AI ready
Considering which team members are best placed to enable with AI tools
Gauging quote conversion percentages to understand the upside
When those questions are addressed carefully, growth does not require radical reinvention — only courage to try and better alignment between people and technology.
This whitepaper draws on published customer case studies and performance analysis from TourConnect AI resources, including Across Australia, Pacific Destinations NZ, AC Group UK, and Tourvest.
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