AI: moving from experimentation to organisational integration

AI is universally deployed but full integration remains rare. This report examines the barriers and opportunities executives face in embedding AI effectively.

AI has transitioned from ambition to actionable deployment across industries. Most organisations are now leveraging its potential, yet the true challenge lies ahead.

HTEC, an AI-driven software and hardware design service provider, has released its Executive Summary: A Cross-Industry View of the State of AI in 2025. This research seeks to provide insights into how senior leaders are handling the next stages of AI transformation, a journey where scaling value remains elusive.

The report highlights a clear inflection point. While AI adoption is universal, full integration is uncommon. Only 45% of executives report AI is fully embedded across various functions. Most organisations experience AI as isolated initiatives rather than a cohesive operational model.

HTEC observes that proving AI's effectiveness is no longer the hurdle. The challenge is integrating promising applications into workflows that deliver consistent ROI.

Many leaders attribute stalled progress not to model performance, but to integration issues. Embedding AI into existing systems is the top barrier, as cited by 43% of executives.

With limited internal resources, executing an AI strategy becomes a bottleneck. Organisations are turning to specialised partners and platforms to mitigate these challenges, thereby focusing internal resources on creating substantial value.

Edge AI is rapidly becoming mainstream. With 92% of executives familiar with its capabilities, there is a strong push to deploy AI closer to where data is generated. This move enhances security, resilience, and regulatory control in constrained environments.

Executives are planning a mixed approach—integrating external partnerships with selective in-house development to ensure speed without sacrificing control.

Leaders recognise the urgency. Failing to seize AI and edge opportunities could delay organisational progress by nearly two years.

As a response, there's an industry-wide rush towards a one- to three-year timeline for validating cases, developing enterprise roadmaps, and embracing AI-enabled revenue streams.

However, confidence is fragile. Only a quarter of executives believe in their rapid AI adoption and scaling ability, while a significant portion struggles with value capture or admits falling behind.

Conclusively, addressing structural, operational, and leadership barriers is crucial. Without action, AI momentum risks turning into a lost advantage.

Lawrence Whittle, Chief Strategy Officer at HTEC, explains that achieving success requires setting ambitious goals, rethinking processes, and scaling AI through comprehensive enterprise roadmaps, with AI integrated as a central operational strategy rather than as isolated initiatives.

Despite security concerns, organisations are advancing with AI deployment, underscoring governance...
Advantech and SecEdge collaborate to support security for AI models at the edge, including use in...
Oracle has unveiled Fusion Agentic Applications, a suite designed for outcome-driven execution in...
Advantech has partnered with Qualcomm Technologies to advance edge AI with the SKY-641E3 server,...
Snowflake introduces Project SnowWork, an AI platform aimed at accelerating workflows and...
Salute teams up with Phaidra to support AI operations in high-density data centres with operational...
SailPoint introduces a novel AI governance solution to monitor and control unauthorised AI tool...
Scality's research reveals challenges in scaling AI infrastructure, highlighting storage's critical...