The Human Touch in the Age of AI

Artificial intelligence has quickly evolved from experiment to infrastructure. Just two years after its explosive rise, AI has become an integral part of how we work, communicate, and innovate.

According to McKinsey, 78% of organizations now use AI in at least one business function, up from 55% the year before. Meanwhile, the number of employees using AI at work has doubled in two years, from 20% to 40% (Anthropic Economic Index, 2025).

But beneath this rapid adoption lies a deeper question: how do we preserve the human touch in a world driven by algorithms?

The Double-Edged Acceleration

AI has brought unprecedented speed to the way businesses operate. Marketing teams generate campaigns in hours, customer support departments handle inquiries 24/7, and developers write code with AI-powered assistants that complete lines before they’re even typed.

These advancements are impressive. They’re also seductive. Efficiency feels like progress — but when everything becomes automated, something vital risks getting lost.

As Groove Technology’s CEO, Matt Long, notes, “We’re replacing one frustrating experience with another. AI can make us faster, but not necessarily better. The winners will be the companies that scale with AI and still keep the human touch.”

In other words, automation can’t be the end goal. Technology should make interactions smoother, not soulless.

When Efficiency Backfires

Think about the modern customer-service experience. A few years ago, long hold times were the biggest frustration. Now, instant chatbots respond in seconds — but often without context or empathy. The result? A new kind of frustration.

The same pattern appears across industries. Automated recruitment tools can screen candidates faster, yet inadvertently filter out promising talent because nuance is lost in a résumé. Generative tools can produce endless marketing content, but much of it sounds the same — polished, yet impersonal.

This phenomenon is what Matt calls AI normalization: the flattening of experience. Everything looks efficient, but feels generic. Businesses risk blending into the noise, creating interactions that are fast but forgettable.

The lesson is clear. AI’s role shouldn’t be to replace human effort; it should elevate it. The question leaders must ask is not “what can AI do for us?” but “what should AI do for us — and what should remain human?”

Accountability: The 16 Percent That Matters

No matter how sophisticated AI becomes, it will never be infallible. Even with 84% accuracy (IEA analysis), that remaining 16% carries risk — and responsibility.

In finance, a small error in automated credit scoring can deny someone access to vital funds. In healthcare, a misclassified diagnosis could impact treatment. Even in software development, a flawed prediction from an AI-driven testing system can lead to downtime or lost revenue.

The risks are not theoretical. A recent Deloitte Australia case highlighted how even the most reputable firms can be affected. Deloitte repaid nearly $98,000 — more than 20% of a $440,000 fee — to the federal government after an AI-generated assurance report contained factual errors and had to be reissued (Business Insider, 2025). The incident underscored a growing truth: while AI may enhance productivity, ultimate accountability still lies with humans.

So who takes responsibility when AI gets it wrong?

That’s where the concept of the human in the loop becomes essential. AI should support decision-making, not replace it. Humans provide the empathy, judgment, and accountability that no algorithm can replicate.

At Groove Technology, this mindset guides how we use AI internally. Whether enhancing productivity or supporting software testing, every AI-assisted process still includes human review. Data privacy, quality assurance, and context-based reasoning remain firmly in human hands. Because automation can process information — but only people can interpret meaning.

The Evolving Role of Engineers

Few professions feel AI’s impact as directly as software engineering. Tools like GitHub Copilot and ChatGPT-based coding assistants can now write, refactor, or test code autonomously. This has led to a new reality: AI won’t replace developers — but developers who use AI will replace those who don’t.

AI-assisted development allows engineers to complete tasks up to four times faster, accelerating release cycles and freeing time for higher-level architecture or product design. But that speed comes with a new responsibility: maintaining quality, ethics, and creativity in an increasingly automated pipeline.

For outsourcing companies like Groove Technology, this shift brings opportunity, not threat. Faster development doesn’t reduce demand for engineers — it increases demand for innovation. As projects move from simple builds to complex, integrated solutions involving cloud, data, and AI components, skilled engineers remain indispensable.

Matt Long summarizes it simply: “Faster software engineering doesn’t reduce opportunity. It unlocks faster innovation.”

Balancing Automation and Empathy

Leaders across industries face the same dilemma — how to scale intelligently without dehumanizing their business. It’s a balance between speed and sensitivity.

Automation can make organizations more productive, but empathy keeps them relatable. Clients remember when a partner listens, understands, and acts with care. Employees stay loyal when technology helps them, not when it replaces them.

That’s why leadership in the AI era requires a mindset shift. It’s no longer enough to ask, “How can we use AI to grow?” The better question is, “How can we use AI to help people thrive?”

This philosophy runs deep within Groove Technology’s culture. From project management to product delivery, the company integrates AI where it adds real value — while keeping people at the center. Internal discussions often circle back to the same principle: the best technology is invisible; it empowers, but never replaces.

Data, Trust, and Responsibility

As organizations rush to adopt AI, another critical issue has emerged — data governance.

Matt points out that for outsourcing businesses, handling sensitive client data adds another layer of complexity. “Data sovereignty, privacy, and protection — not only of customer information but also of our employees’ data — have been our top priority in developing our AI strategy,” he says.

Every AI system is only as trustworthy as the data it handles. Building confidence means not just complying with regulations but embedding transparency and responsibility into every process. In the long run, clients will choose partners they can trust — not just those who automate best.

Looking Ahead

The conversation around AI is evolving from excitement to maturity. Businesses have learned that adopting AI isn’t about keeping up — it’s about showing up differently: smarter, faster, but also more human.

The next phase of AI will be less about automation and more about augmentation — enhancing human creativity, decision-making, and connection. The organizations that thrive will be those that see AI as a collaborator, not a competitor.

As Matt Long puts it, “AI may help us scale, but empathy will keep us relevant.”

Matt Long – CEO of Groove Technology, he shares his perspective on how businesses can leverage AI responsibly while preserving empathy and human connection.

Mai Nguyen – General Director of Groove Technology Vietnam, she focuses on empowering people and guiding teams to use technology as a tool for growth and collaboration.