Across the sector, AI adoption has accelerated rapidly. What was once experimental is now embedded in everyday operations, from forecasting and pricing to customer service and personalisation.
NashTech’s latest custom software development in consumer, retail and hospitality report reinforces this shift. Most organisations are already investing in AI, and, critically, many see it as a driver of broader change, with 96–98% recognising that AI is accelerating the move towards more flexible, custom-built solutions.
However, while adoption is widespread, scaling impact remains a challenge. Many organisations are still struggling to move beyond isolated use cases, at a time when consumers expect seamless, personalised experiences at every touchpoint.
NashTech’s research highlights a clear gap between intent and execution. While investment levels are high, a significant proportion of organisations report difficulty scaling AI beyond isolated use cases, particularly when it needs to operate across multiple systems and touchpoints.
This reflects what we see more broadly across the industry. Many organisations are still applying AI within individual functions rather than embedding it across the full customer journey.
The shift taking place in 2026 is that clear success is no longer defined by how much experimentation is happening, but by how effectively organisations can scale and operationalise it.
Question for David:
Have consumer and retail organisations genuinely moved beyond AI experimentation, or do you still see initiatives struggling to scale across the business?
In short, we’ve moved beyond experimentation with intent, but not yet to execution at scale.
Most organisations are clear that AI is now a core part of the roadmap, with strong expectations of near-term impact and adoption. So, the shift isn’t about willingness; it’s about readiness. The blockers are consistent: legacy integration, fragmented data and governance uncertainty are slowing the move from pilot to repeatable value.
There are already clear areas where AI is delivering results.
Within our latest report, the most immediate impact is being seen in operational efficiency, with organisations using AI to improve forecasting, streamline operations, and reduce manual processes. This aligns with wider industry findings, where retailers are seeing 5–15% revenue growth and up to 30% cost reduction from AI-led initiatives.
However, more transformative use cases, particularly those that reshape the customer experience, are still evolving. While customer experience is the primary driver of AI investment, many organisations are still in the early stages of delivering truly seamless, end-to-end journeys.
Question for David:
Where are you seeing AI deliver real commercial value today, and where is the industry overestimating what’s achievable in the short term?
There are areas where ROI is already being tracked and justified at board level. For example, customer experience and personalisation, productivity and operational efficiency
Where the industry is overestimating things is at the more complex end, particularly agentic AI and autonomous decisioning. Broadly, assistive AI is delivering value today; fully autonomous AI at scale is still early, and in many cases ahead of the underlying foundations.
NashTech’s report points to a consistent set of barriers. Integration challenges, fragmented data, and the limitations of legacy platforms are among the most commonly cited issues preventing AI from scaling effectively.
This is not surprising. Many consumer businesses rely on a mix of legacy systems, packaged platforms, and point solutions in environments that were not designed to support dynamic, real-time, AI-driven experiences.
Industry research shows that these legacy environments can lead to disconnected data, slower innovation cycles, and limited ability to scale new capabilities, directly impacting growth and competitiveness. At the same time, a large proportion of IT investment is still tied up in maintaining these systems, limiting organisations’ ability to innovate.
Question for David:
Why are traditional platforms starting to fall short, and when do organisations begin to outgrow off-the-shelf solutions?
The core issue is that most traditional platforms weren’t designed for the level of flexibility, speed and integration now required. Across the consumer sectors, there’s a consistent view that commercial off-the-shelf platforms struggle when differentiation matters, real-time integration across multiple systems is needed, and AI/data-driven decisioning becomes central to operations.
NashTech’s report highlights three areas that consistently separate organisations that can scale AI from those that struggle:
Without these foundations, even well-funded AI initiatives fail to deliver consistent value.
This is reinforced by broader industry trends, in which fragmented systems and inconsistent data continue to limit AI’s effectiveness across the sector. At the same time, expectations are rising beyond retail. In hospitality, AI is enabling more personalised and anticipatory experiences, raising the bar for what consumers expect across the board.
Question for David:
What does being ‘AI-ready’ look like in practice, and what separates organisations that can scale quickly from those that can’t?
AI-ready doesn’t mean having models in production; it means having the foundations to scale them reliably.
In practical terms, it comes down to:
NashTech’s report highlights a clear shift in mindset. Rather than relying solely on off-the-shelf platforms, organisations are increasingly investing in custom software to bridge gaps, connect systems and enable greater flexibility.
This is driven by a simple reality: experience has become a key differentiator. And delivering differentiated experiences requires technology that can adapt to specific business models, customer journeys, and data environments.
Custom software is therefore evolving from a delivery choice to a strategic enabler, supporting integration, scalability and innovation in ways that standard platforms often cannot.
Question for David:
How is the role of custom software evolving and why is it becoming more important as experience becomes a key differentiator?
Custom software has moved from optional innovation to a core business capability, driven by clear links to customer experience and commercial outcomes.
As experience becomes the main differentiator, standard platforms struggle to keep pace. They still work for core systems, but they can’t offer the flexibility or control needed at the experience layer.
So increasingly, custom is where organisations differentiate, embedding AI, shaping journeys and moving faster than vendor roadmaps allow.
NashTech’s research makes one thing clear: success will depend on building the solid foundations required to make AI work at scale.
As that shift continues, custom software is emerging as a critical enabler, helping organisations move beyond experimentation and deliver the connected, experience-led transformation the market now demands.
Is your organisation set up to deliver real value?