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From AI uncertainty to a quantified AI roadmap

Case Type

Strategy-led Case

Industry

Travel

Company Snapshot

→ Mid-market travel group

→ ~€180M revenue

→ 1,095 agents

→ 700+ agencies

Areas Analysed

->
Distribution Networks
->
Internal Communication
->
Operations & Delivery
->
Sales
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Context

Grupo Newtour is one of the largest travel distribution groups in Portugal, operating multiple brands and networks, including franchise and independent agencies. In 2024 alone, the group grew 21%. But growth amplified complexity.

Across 1,095 agents and multiple business units, operations relied heavily on:

  • Manual intermediation between clients and suppliers
  • Fragmented lead management across email, phone, WhatsApp and social media
  • Multiple disconnected systems (SIGAV, Optigest, Odoo, Primavera)
  • Manual reporting and performance consolidation
  • Non-standardized quotation processes

AI had been discussed internally.

But previous attempts had not delivered impact.

‍

‍Leadership needed clarity before committing to technology again.

Core Challenge

The AI Imagination Gap

Newtour did not lack ideas. It lacked prioritization and quantification.

Key barriers

  • Multiple areas with AI potential, no clear starting point
  • Inefficiencies known but not economically quantified
  • Fragmented systems across group companies
  • Previous AI initiative that failed to reach objectives
  • Fear of “implementing technology before fixing the fundamentals”

    The risk was clear

    Invest in AI tools without a validated business case.

    There are many tasks today that we still execute in a traditional way, even though AI can already support them. What became clear during the AI Value Discovery is that this is not about replacing people, it’s about freeing them.
If we can automate operational layers, especially for coordinators and directors, we create space for strategic thinking, creativity, and better decision-making. That shift in focus is where the real transformation begins.

    Diana Laranjeira
    Marketing & Communication
    Umain Approach

    AI Value Discovery

    Umain conducted a structured, business-first AI Value Discovery engagement.

    01

    Executive Alignment

    Mapping strategic priorities and securing leadership consensus.

    02

    Immersion Session

    Demystifying AI, aligning terminology, clarifying realistic applications.

    03

    Design Thinking Workshop

    Full-day collaborative session identifying high-impact opportunities across business areas.

    04

    Value Delivery Roadmap

    Quantification of effort, complexity, ROI, and sequencing.

    Key Outcomes

    6 Prioritized AI Initiatives

    Internal Knowledge AI Assistant

    Fill-in
    Fragmented communication across WhatsApp, Teams, email and intranet.

    Current State

    → 5 interruptions per person per week

    Target Impact

    → 90% adoption

    → Drastic reduction in repetitive internal queries

    Autonomous Multi-Supplier Pricing Engine

    Moonshot
    Manual comparison of travel suppliers.

    Current State

    → 30 minutes to 8 hour per quotation

    Target Impact

    → 50% reduction in creation time

    → Significant uplift in agent productivity

    → Higher deal optimization

    AI-Assisted Quotation Standardization

    Fill-in
    1,095 agents creating 10–15 quotations per day without standardized templates.

    Current State

    → 15 minutes to 1 hour per quotation

    Target Impact

    → 20% reduction in creation time

    → Increased brand consistency

    Automated Executive BI

    Quick Win
    Manual consolidation of fragmented reporting.

    Current State

    → 6h/week per director spent compiling reports

    → No centralized triage

    Target Impact

    → 4h/week saved per director

    → Standardized real-time dashboards

    Unified Lead 
Intelligence System

    Quick Win
    Leads fragmented across multiple channels.

    Current State

    → 8h/day × 2.5 people × 49 branches

    → No centralized triage

    Target Impact

    → 15–20% increase in conversion rate

    → 5–10% additional selling time per agent

     Intelligent Request Automation

    Quick Win
    Manual intermediation between client and supplier with no technical added value.

    Current State

    → 7 people

    → 15-30 minutes per day each

    Target Impact

    → 80% time reduction (progressively towards full automation)

    Intelligent Request Automation

    Quick Win
    Manual intermediation between client and supplier with no technical added value.

    Current State

    → 7 people
    → 15 - 30 minutes per day each

    Target Impact

    → 80% time reduction (progressively towards full automation)

    The most important result was not automation.
    It was clarity.

    • A sequenced roadmap
    • Reduced risk before investment
    • Alignment across leadership, operations and IT
    • Quantified business cases
    • Clear prioritization of initiatives

    Executive Productivity

    4 hours/week

    time reduction depending on use case

    • Improved decision speed through centralized BI

    Operational Efficiency

    15% to 80%

    time reduction depending on use case

    • Hundreds of thousands of manual hours potentially reduced annually
    • Quick wins expected to deliver visible results within 1–3 months post-implementation

    Revenue & Conversion

    15% to 20%

    time reduction depending on use case

    • Increased agent availability for high-value selling activities

    Decisions Enabled

    AI stopped being a concept. It became a structured investment roadmap.

    We don’t see AI primarily as a cost-cutting tool. We see it as a way to become more efficient with the structure we already have. Our goal is simple: to do more with the same, and to do it better for the end customer. AI helps us optimize internally so we can strengthen what truly matters: delivering value to the client. Efficiency is important. But value creation is our real focus.

    Carlos Baptista
    Executive Committee

    Many organizations jump from ambition to implementation.

    Chose a different path: clarity before code.

    Ready to turn AI ambition into a roadmap?

    Start with AI Value Discovery
    Discuss your use case with our team→