As enterprises across Southeast Asia accelerate their adoption of artificial intelligence, AI is increasingly embedded into everyday workflows from compliance checks to finance operations.
While the technology is delivering real efficiency gains, it is also giving rise to less visible but growing problems like low-quality, poorly integrated AI output that creates the illusion of productivity without delivering real value.
Kazunori Fukuda, Managing Director of Sansan Thailand, shares with iTNews Asia insights on how this phenomenon often referred to as “AI slop” is emerging as a new enterprise risk, which can damage an organisation’s credibility and trust.
Southeast Asia is proving to be an AI-forward region, with companies eager to weave automation into core business processes, said Fukuda, who added that the most tangible gains are being seen where AI is embedded into routine but high-volume workflows.
“In Singapore, financial institutions are widely using AI to streamline compliance checks,” Fukuda said. “This weaving AI into conventional workflows helps reduce manual intervention, making processes faster and more accurate without downsizing teams.”
In Thailand, similar momentum is visible in finance and back-office operations. “We’re seeing more companies using AI-embedded cloud services for automating invoice management and approvals. It saves man-hours, eliminates human error, and leads to faster monthly closing,” he added.
However, Fukuda warned that these gains are not automatic and that poorly planned deployments can add complexity rather than clarity.
When AI looks productive but delivers poor outcomes
The rise of AI slop reflects a deeper issue in how enterprises approach automation. Fukuda described it as the result of adopting AI tools without sufficient customisation, iteration, or organisational alignment.
“AI slop often occurs when companies implement off-the-shelf AI solutions and accept their defaults without taking the time to customise for specific needs,” he said. “Users may treat AI like a vending machine, without iteration and a spirit of exploration.”
In practice, this leads to outputs that appear efficient but fail under real-world conditions.
This results in AI-generated outputs that look efficient on the surface but are of poor quality, leading to errors that require human intervention anyway,” he explained, citing cases where AI struggled to interpret fine print in complex invoices, causing processing errors.
Speed without strategy creates hidden costs
One of the key drivers behind AI slop, Fukuda noted, is the tendency to treat AI as a quick fix rather than a strategic capability.
Many companies select tools without carefully considering whether they suit the specific challenges of their industry. There is often a cultural disconnect where companies may view AI as a quick fix rather than a tool to enhance human capabilities.
- Kazunori Fukuda, Managing Director of Sansan Thailand
This approach not only reduces the quality of AI output but also creates what Fukuda described as strategic debt - new layers of cost, governance complexity, and operational friction.
When AI initiatives move faster than an organisation can align them with strategic intent, warning signs emerge. AI projects become isolated in single teams, creating silos where automation doesn’t actually drive value creation, he explained.
Fukuda emphasised that avoiding AI slop requires more than better tools - integration, governance, and people.
“To safeguard against AI slop, leaders must focus on strategic integration, employee upskilling, and customisation,” he said. “AI tools must be integrated into core business processes and not used in isolation.”
For instance, at Sansan, employees across functions are onboarded to AI through hands-on programs designed to help them apply the technology to real business problems.
“Everyone needs to understand AI’s capabilities and limitations. That’s how you ensure AI enhances substance rather than generating superficial volume,” Fukuda said.
For leaders embarking on AI-driven transformation, he advised starting with fundamentals rather than technology. He said they should first ask: “How does AI align with our overall business strategy?” and “What specific problems is AI actually solving?”
In the first six months, he noted, warning signs often include poor integration with existing workflows, resistance from employees, and a lack of clear, measurable value from AI initiatives. “AI is not just a tool for speed,” Fukuda added. “It’s a tool for strategic growth, if it’s applied thoughtfully.”
As Southeast Asia continues to adopt AI at pace, the challenge for enterprises will be to ensure productivity gains are genuine, sustainable, and meaningful rather than being diluted by the growing risk of AI slop.
