Virgin Atlantic’s Blueprint for AI Success

Amidst widespread AI project failures, Virgin Atlantic’s data and AI chief shares five crucial insights for successful adoption. Learn how their strategic approach and cultural focus turn AI potential into tangible business advantage.

The promise of artificial intelligence echoes through boardrooms and investor calls, a siren song of efficiency, innovation, and unprecedented growth.

Yet, for many organizations, the reality is a far more sobering tale.

A significant chunk of AI projects, an alarming 60% according to Gartner, are destined for the scrap heap by 2026, often due to a fundamental lack of readiness in data management practices.

Almost two-thirds of businesses confess they aren’t even sure if their data foundations are robust enough to support these ambitious AI ventures.

It’s a paradox: immense potential, yet widespread failure.

Amidst this landscape of dashed hopes and abandoned initiatives, some pioneering organizations are charting a different course.

Virgin Atlantic, a brand synonymous with customer experience and operational excellence, stands out.

Richard Masters, the airline’s VP of Data and AI, articulates a refreshingly simple philosophy: “We want people to have a great experience on the plane, and exploiting AI is about whatever we need to do to deliver those objectives.”

This clarity of purpose, he suggests, is the bedrock of their successful AI journey, a journey he illuminated at a recent Databricks roundtable in London, offering five crucial insights for businesses navigating the complex world of AI.

The first, and perhaps most transformative, step is to actively expose people to new tools.

AI isn’t a new concept in the airline industry; predictive analytics for load factors, revenue, and aircraft reliability have been standard for years.

Masters notes that the evolution of statistical analysis through AI has been gradual, but with a recent, accelerating upward trend.

The true inflection point, he argues, was the public release of ChatGPT in November 2022.

This moment demystified AI, making advanced conversational capabilities accessible to the masses.

Suddenly, non-analytical teams across Virgin Atlantic began to grasp AI’s potential, envisioning how it could reinterpret data, explain complex concepts, and provide analytical insights to parts of the business previously untouched by such sophisticated tooling.

Masters and his team seized this momentum, actively exploring how these democratized tools could boost productivity and operational effectiveness, even pushing insights through internal bots on their data platform.

However, simply exposing people to new tools isn’t enough; the true challenge lies in ensuring these tools answer key business questions effectively.

For some applications, the return on investment (ROI) is crystal clear.

Dynamic pricing tools, like Virgin Atlantic’s partnership with Fetcherr, or predictive maintenance and fuel optimization, offer easily quantifiable savings or revenue generation.

These are the “easier targets,” as Masters puts it.

But for more nuanced areas, such as improving decision-making processes where ROI is less tangible, his team has pivoted.

They’ve focused on preparing their Databricks data platform to be “ready for the questions to come in,” ensuring they can swiftly provide the right algorithm or data set.

This proactive approach allows them to analyze net promoter scores, combine survey results with in-flight experience data, and answer a multitude of smaller, yet critical, questions without cumbersome prioritization exercises.

The platform, in essence, becomes an agile engine for continuous inquiry.

The third vital strategy involves establishing a unified approach to AI adoption.

The market is awash with “noise” from tech vendors pushing their latest AI-enabled systems and services, creating a cacophony that can overwhelm even the most focused organization.

Virgin Atlantic combats this by establishing a robust “front door” process for assessing new AI suggestions.

A weekly gathering of specialists – architects, business analysts, and the central product management office – meticulously explores technology proposals.

This is then elevated to a higher-level assessment by Masters and his VPs for technology, digital, and data.

Crucially, these discussions extend to other senior executives, such as the VP of customer journeys and engineering, to ensure proposed technologies align with broader business strategy.

This joined-up approach ensures resources are allocated wisely, preventing redundant purchases and fostering cross-silo collaboration.

Fourth, Masters emphasizes the importance of exploiting your platform.

Airlines traditionally grapple with siloed data, holding customer and operational information in disparate systems.

This fragmented approach severely hampers cross-business initiatives.

Virgin Atlantic proactively addressed this by consolidating its enterprise information within Databricks’ Unity Catalog.

This unified data platform has been revolutionary, enabling the airline to run intricate simulations and predictive models with unparalleled agility.

In the event of a disruption, for instance, they can instantly ascertain the number of connecting passengers at a specific airport, assess their tight-connection risks, and dynamically deploy ground teams to assist.

This granular, real-time insight, rolled up to any dimension required, transforms operational responsiveness, shifting from reactive scrambling to proactive, informed action.

Finally, and perhaps most profoundly, digital leaders must keep fostering curiosity.

Masters observes that data teams often become overly engrossed in the intricacies of platforms and tooling.

However, as technology evolves, the specifics of building a better database or connecting systems become less of a day-to-day priority.

Data now appears on platforms almost automatically, and connections are increasingly seamless.

This shift frees data leaders to step back from the technical minutiae and, instead, cultivate a deep curiosity about the organization itself.

“The focus, instead, becomes being curious about the organization you’re in, and thinking about what to do,” Masters explains.

By removing the technical “noise,” leaders can hone in on what truly matters, articulating those priorities back to their teams and instilling a similar spirit of inquiry.

Virgin Atlantic’s journey underscores a critical lesson: AI success isn’t solely about sophisticated algorithms or cutting-edge technology.

It’s about a strategic shift – from merely implementing AI to using it as a catalyst for deeper business understanding, fostering an organizational culture that embraces curiosity, unifies efforts, and leverages data as a strategic asset.

In a world where AI projects are prone to failure, Masters’ pragmatic approach offers a compelling blueprint for turning technological potential into tangible business advantage.