Enhanced humans: what to expect from the AI-augmented workplace

Imagine a future where your potential isn’t limited by time, task or knowledge. This is the era of “enhanced humans”, a concept identified as a key theme in the NTT DATA Technology Foresight 2025 report. Published annually, the report acts as a compass, pointing to the latest technological trends that NTT DATA researches and analyzes.

The concept refers to the amplification of human abilities through synergistic collaboration between people and machines, using technologies such as AI, machine learning and automation. 

Rather than replacing people, human–technology integration is about boosting your employees’ productivity, improving the quality of their output and arming them with the skills to handle more complex and value-generating tasks.

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Technologies to watch

A range of technologies is steadily enabling the integration of AI into daily work. According to our report, the main ones to watch include:

• Leading large language models (LLMs) like GPT-4, Google’s Gemini and NVIDIA’s Nemotron-3 are increasingly being refined for different applications, including real-time processing and on-device use in industries like education and customer service.
• GPT-4o, the latest version of OpenAI’s Generative Pre-Trained Transformer (GPT), supports multimodal inputs, real-time conversations and memory learning. It also comes with advanced translation and emotion detection capabilities.
• OpenAI’s o1 model excels in advanced reasoning for complex tasks but operates more slowly and at higher costs compared with GPT-4o. Unlike GPT models, o1 models are trained using reinforcement learning techniques to “think before they answer”, and they produce long internal chains of thought.
• Retrieval-augmented generation (RAG) improves LLMs by retrieving relevant external information and integrating it into responses to improve accuracy, contextual understanding and cost-effectiveness. However, RAG comes with challenges such as retrieval quality and ethical considerations.
• Digital humans (also called AI avatars) are becoming more realistic and interactive, with applications in customer service, entertainment and healthcare thanks to real-time capabilities like the detection of facial expressions and emotions.

4 strategies for success

As GenAI is infused into day-to-day life, balancing responsibility and innovation is becoming a moral and strategic necessity. The report identifies four core strategies for successful human–technology integration in the workplace and the continued adoption of this trend.

1. Deploy safety and compliance guardrails

Tech-enabled workforce AI safety and compliance will be decisive success factors if you want to expand your organization’s use of AI. Systems will need to be efficient, fair and compliant with evolving global data protection laws such as the European Union’s General Data Protection Regulation.

Technical measures such as differential privacy (which lets organizations analyze and share data while protecting the privacy of individuals within the dataset), federated learning and bias-detection tools can help minimize these risks. Equally, approaches such as SHapley Additive exPlanations (SHAP) — a way of explaining the output of machine-learning models – and local interpretable model-agnostic explanations (LIME), which approximate black-box machine-learning models to explain individual predictions, can make decisions more transparent while safeguarding against cyberattacks.

2. Prioritize organizational enablement for AI adoption

Organizational enablement through AI refers to the targeted use of AI to transform culture, people and processes to improve efficiency and inspire innovation. Increasingly, we’ll see organizations integrating AI into areas such as human resources, the supply chain, financial planning and decision-making processes to create competitive advantages.

Humans and machines need to cooperate and collaborate to exploit the full potential of AI, but this will also rely on effective change management and training. Your employees need to be comfortable and confident working with AI systems.

3. Start making AI assistants part of daily life

A great way to start integrating AI into your workplace is with GenAI assistants that work alongside employees to analyze large data sets, summarize complex information and generate personalized content. Through natural language interaction, they can help your employees access the data they need and support collaboration and productivity — for example, by automatically generating meeting summaries and offering suggestions on the prioritization of tasks.

These technologies are an excellent way to start building confidence around human–machine integration within your organization.

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4. Welcome AI as a partner in software development

Encourage your developers to experiment with GenAI when they’re creating code, designs and applications. Emerging models can help them develop software faster and more cost-effectively, while AI-assisted integrated development environments (IDEs) can offer real-time code suggestions.

Techniques such as transfer learning and reinforcement learning can improve the quality of the generated software components. GenAI can also automate DevOps processes and improve security through AI-driven code analysis and security checks.

Together, these capabilities will help your developers start working in a more agile and innovative way.

Navigating the risks and blind spots

Like almost every technological breakthrough, human–technology integration comes with potential risks. Let’s explore some of these:

Regulatory lags and oversight

What if regulation struggles to match the pace of AI development?

As AI fuels the integration of technology with human workplace tasks, it’s creating an environment that is conducive to innovation. However, regulatory frameworks governing its responsible use may be lagging behind. There’s a risk that advances in augmenting human capabilities could continue unchecked until regulations eventually catch up to provide the necessary guardrails.

Given the higher levels of regulatory attention on the finance and healthcare industries, they are likely to lead the way in safely integrating AI and set new standards for technologies that augment human abilities. However, because other sectors will initially lack the same level of oversight, it could lead to the uneven application of AI.

Upskilling divides and employment instability

What if the race to upskill with AI creates both champions and stragglers in society?

As industries integrate AI, the divide between those who are given the opportunity to improve their skills and those who aren’t could deepen, affecting social equity. This highlights the need for comprehensive, accessible training programs through which everyone can benefit from these developments, not just those already at an advantage.

Job security

While the growth of the gig economy through AI will introduce opportunities for greater flexibility and diversity that support personal and professional growth, it could introduce challenges in job security. You’ll need to rethink your traditional employment model and create work structures that balance flexibility with stability for a range of workers.

Where to next?

Given the rapid pace of AI advancements, staying ahead will require constant adaptation and the integration of the latest tools and techniques. As concerns regarding AI ethics and bias increase, you need to put in place transparent and explainable AI systems and comply with new laws governing the use of these systems.

Because AI technologies won’t replace people but rather augment their abilities, critical thinking and targeted questioning remain essential. Other critical questions include ownership of AI models and the distribution of value generated by AI services.

Closing thoughts

To address the potential challenges of integrating AI into your workplace, using GenAI-powered personas or avatars to analyze different scenarios for the future of your organization has proved to be a powerful approach.

These personas — which are created with technologies like multimodal GenAI, natural language processing and emotion AI — will facilitate more immersive and interactive ways of simulating business environments, helping you mitigate risk through scenario-based planning.

While some uncertainty will remain, exploring these scenarios will reduce the risk of blind spots down the road.

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