AI in insurance: from paperwork to end‑to‑end, data‑driven workflows
In insurance, AI is no longer an experiment sitting in a lab; it is being wired directly into the full policy lifecycle. At Vertafore’s Accelerate 2026 conference, the company unveiled its Velocity AI Platform, industry‑specific AI agents and tools like ReferenceConnect AI to support submissions, quoting, servicing and client engagement across agencies, MGAs and carriers. The goal is what Vertafore calls “Distribution Velocity”: using core digital platforms and unmatched data to remove friction in how policies are sold and serviced. For Malaysian insurers, this illustrates what true AI in insurance looks like: automated data gathering for underwriting, faster document production, and claims workflows that can triage and respond in minutes, not days. Routine tasks like certificate management are being streamlined, freeing human agents to focus on complex risk advice. The implication for local professionals is clear: value shifts from filling forms to interpreting insights and building relationships.
AI in hospitality and transport: guest journeys, search and new power brokers
Hospitality and passenger transport, long seen as “high-touch, low-tech” sectors, are being quietly re‑architected by AI. RBS’s acquisition of Zeko, an AI-powered guest engagement platform, shows how AI in hospitality is moving into the core of the guest journey. Zeko automates pre‑arrival messaging, digital check-in, WhatsApp-based concierge and AI upselling, with some hotels reporting up to 20 percent revenue lifts from smarter ancillary sales. At the same time, AI driven search is reshaping visibility in the motorcoach and bus industry. Instead of long lists of operators, AI search tools now surface direct answers drawn from a small set of sites, favouring digital‑savvy brokers whose content spans multiple markets. As CEO Christian Riddell warns, operators who are not included in those AI-crafted answers risk becoming invisible. For Malaysian tour, charter and hotel operators, this underscores a new power dynamic: those who master AI-optimised content and data capture will own the customer relationship—and the margins.
Planning and retail: AI tools turn forecasts into real‑time decisions
Retailers and brands are also turning to AI planning tools to escape the old “guessing game” of seasonal forecasts. In fashion, where late receipts, social-media-fuelled trend shifts and regional differences make demand volatile, planners have traditionally made a few big bets months in advance and hoped forecasts held. Experts speaking at a Sourcing Journal webinar highlighted that this model is breaking down as teams juggle more SKUs, channels and margin pressure. AI systems are now being used to continuously read signals—from sell-through rates to regional demand spikes—and recommend adjustments in-season, such as reordering winning styles, shifting stock between stores or dialing promotions up or down. For Malaysian retailers, the lesson is that AI planning tools are less about flashy dashboards and more about connecting design, merchandising, supply chain and finance data into a single, adaptive decision engine that protects margins while reducing waste and stockouts.
AI transportation market and aviation: efficiency, safety and Asia-Pacific momentum
Beyond individual operators, AI is becoming infrastructure in the broader AI transportation market and aviation ecosystem. Market researchers project strong growth as AI optimises traffic flows, logistics and predictive maintenance. AI-powered traffic management has already helped cities like Los Angeles cut congestion by around 30 percent, while logistics firms using AI report double‑digit cost reductions through better routing and demand prediction. In aviation, AI is being integrated into flight scheduling, customer service chatbots, predictive maintenance and even future air-traffic management. The global artificial intelligence in aviation market is forecast to grow at a compound annual rate above 25 percent from 2026 to 2033, driven partly by commercial airlines seeking higher safety and reliability. Asia-Pacific, including Malaysia, is highlighted as a key growth region as airlines and ground operators modernise fleets and infrastructure. For local transport and aviation professionals, the opportunity lies in data literacy, operations analytics and safety-focused AI deployment—not just in piloting new apps.
Jobs, myths and Malaysian upskilling: what work looks like next
As these examples show, AI is changing who does what work—but often in more nuanced ways than public debates suggest. Opinion pieces in education note that many myths about AI at work, such as easy detection of AI-generated writing or one‑off training being enough, are already outdated. Studies show humans are poor at reliably spotting AI output; what matters is how well people learn to collaborate with these systems. Across insurance, hospitality, logistics and retail, repetitive tasks—data entry, standardised emails, basic report generation—are being automated. New demand is emerging for roles that blend domain expertise with AI fluency: claims professionals who can interpret model outputs, revenue managers who fine‑tune guest engagement algorithms, planners who question AI forecasts, and operations leads who translate business goals into data problems. For Malaysian workers, practical next steps include building skills in prompt design, data interpretation, process re‑engineering and digital customer experience—moving from fearing AI to managing and directing it.