By Mike Foster/ As we dive deeper into the themes introduced in my last column (and series opener), I want to share a practical vision of the near future. We are standing at a crossroads: AI is already part of our daily lives, and by 2026 it will be far more ubiquitous in the workflows of travel professionals.
Preparing for that future means not just adopting new tools but learning how to make those tools serve the human strengths that clients still crave. This article imagines a day in the life of a leisure travel advisor in 2026 – one who has embraced early AI collaboration, set clear guardrails, and used technology to amplify judgement, trust, and creativity.
While this future I describe may be wildly wrong, that’s not really the point. My aim is to show what’s possible when human expertise and smart automation work together: faster service, cleaner operations, and more time for the parts of the job machines can’t do. Think of this less as prediction and more as an invitation. A chance for you to imagine your own version of the future, and to brainstorm how you’ll bring it to life with your clients and business.
Meet Maya …
7:58 a.m. – Opening the day: triage, not overwhelm
Maya, a leisure advisor in Toronto, starts with her morning dashboard: overnight price moves, airline alerts, client messages, and a short AI-generated digest of urgent items. The system triages by intent – “date change,” “new enquiry,” “urgent issue” – and highlights two items: a villa tightening its cancellation window and an alert of possible strike activity in Europe.
The AI did the heavy lifting by condensing noise into a one-page brief and pulling relevant policy clauses. Maya’s role is judgement: she sanity-checks the summary, decides what needs immediate action, and prioritizes human touch where it matters. The principle is simple: trust the summary, verify the decisions that affect people and money.
8:40 a.m. – From prompt to proposal: AI drafts, advisor curates
A family enquiry arrives: “Two adults, two kids, March break, Caribbean, good food, snorkelling.” Maya asks her trip-builder co-pilot: “Draft three options in my voice. Focus on boutique properties with interconnecting rooms; avoid red-eye flights.” Within seconds she receives skeleton itineraries: pricing, room types, short copy and alternate dates for better value.
AI supplies the scaffolding, Maya supplies the judgement. She swaps a property after recalling a recent site visit, inserts a trusted local operator for a private reef day, and records a brief voice note explaining her rationale. The system transcribes and embeds the note in the proposal. The outcome feels bespoke, but the time to produce it has shrunk dramatically.
10:15 a.m. – Marketing without losing the human voice
Maya’s content planner suggests a post: “Three ways to keep March break peaceful.” The AI drafts a carousel in Canadian English, pulls two client quotes (with permission) and formats it for social. Maya edits the tone, adds a photo from last summer’s reef trip and replies to comments personally. Rule of thumb: if a tool doesn’t save time, reduce errors or help you sell smarter, don’t use it.
11:30 a.m. – Supplier conversations, sharper questions
A boutique resort pitches a new family program. The co-pilot surfaces Maya’s previous bookings, client feedback and the resort’s historical response times. It suggests smart questions – blackout dates on interconnecting rooms, snorkel access for small children, policies for food allergies. Maya builds rapport, negotiates a “soft” hold and asks the line that opens doors: “If anything slips, please call me directly – not the client.” The AI drafts the follow-up, but Maya’s relationship closes the deal.
1:05 p.m. – Calm in disruption
The European carrier confirms a strike. Maya’s dashboard flags affected clients and offers ranked reroutes. AI drafts clear client messages comparing trade-offs; Maya picks up the phone to talk to the anxious family. Clients remember the call, not the algorithm: reassurance remains a human premium.
2:20 p.m. – Fees, value and You Inc.
Two enquiries ask about planning fees. AI drafts a polite explanation; Maya adds her value statement: “You’re paying for judgement, access, and an advocate when the unexpected happens.” The system handles invoicing and receipts; Maya keeps the conversation human and transparent. Fees are no longer awkward – they are a signal of professional value.
3:10 p.m. – Learning that compounds
A family returns from Barbados. The co-pilot runs sentiment analysis on their feedback, surfaces three “frictions” (airport queue, pool shade, missed allergy note) and suggests supplier briefings and internal updates. Maya writes a handwritten card and includes a photo from the private reef day. That small human gesture is not scalable by a bot – and that’s precisely why it matters.
4:30 p.m. – R&D hour (non-negotiable)
Maya finishes client work but doesn’t log off. She spends 30 minutes in research and development mode: testing a new policy-check tool that reads every quote for gotchas (currency, blackout dates, kids’ club ages, deposit timing). Today the AI missed a villa’s cash-only damage deposit, so Maya logs a bug, updates her own “house rules,” and adjusts her prompts.
She keeps three rules pinned above her desk:
- Always verify money, timing, and age rules manually.
- Never let AI email a client without a human read.
- If you wouldn’t say it in person, don’t let the bot say it for you.
This half-hour isn’t billable, but it compounds. Every tweak she makes now means fewer mistakes and faster service later. By 2030, the advisors who consistently invest in this habit will have trained systems that feel uniquely theirs – quietly amplifying their judgement, not replacing it.
Guardrails for early AI collaboration
Maya’s house rules keep the system honest and safe:
- Consent and privacy: Always disclose automation and get permission to reuse testimonials or photos.
- Double-check money, timing, and legal items: Anything that affects payment, timing or legal obligations receives a human sign-off.
- Bias watch: Don’t let the tool default to the same “popular” options. Rotate sources and cross-verify.
- Voice integrity: Train tools on your actual tone (Canadian spelling, your style). If it doesn’t sound like you, rewrite.
- Kill switch culture: If a tool misfires, stop and revert to manual; clients remember recovery more than the error.
Starter stack (lean and practical)
- CRM and inbox triage that tags intent and flags risk.
- Itinerary builder with LLM co-pilot for first drafts.
- Fare and room monitoring and disruption alerts wired to your calendar.
- Supplier notes database (your IP) updated after every trip.
- Simple content planner that drafts posts in your voice; and you provide the polish.
The takeaway
Between 2025 and 2026 the table stakes shifted: speed and clarity became expected; data became usable for small operators; and human judgement became exponentially more valuable when it was amplified by smart tools. The point is not to “do AI” for its own sake. It’s to design leverage. To create compounding advantage where your judgement, taste and relationships are multiplied by tools that reduce “friction” and reveal better choices faster.
Start now. Set guardrails. Tune your system weekly. By 2030, the advisors who began early will be far ahead. Not because robots replaced them, but because they taught the tools to make their humanity scale. Perfection remains a unicorn. Better – for your clients and for you – is already here.
(After nearly 50-years in the Canadian travel industry, Mike Foster recently retired as the president of Nexion Travel Group Canada, having also served with ACTA, TICO, and other industry organizations, as well as teaching tourism at Fanshawe College, in London, Ont., during his distinguished career).
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