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Why AI strategy is your business strategy: The acceleration toward an AI-native state. Explore executive insights from AI leaders.
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Why AI strategy is your business strategy: The acceleration toward an AI-native state. Explore executive insights from AI leaders.
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Over time, Liantis – an established HR company in Belgium – had built up data islands and isolated solutions as part of their legacy system.
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We ensured that Randstad’s migration to Genesys Cloud CX had no impact on availability, ensuring an exceptional user experience for clients and talent.
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2026 Global AI Report: A Playbook for AI Leaders
Why AI strategy is your business strategy: The acceleration toward an AI-native state. Explore executive insights from AI leaders.
Access the playbook -
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Topics in this article
The digital workplace has transcended simple collaboration tools to become a complete, integrated ecosystem. As organizations embrace the complexities of hybrid work, the physical office must also evolve beyond smart automation to become an intelligent, AI-driven core where predictive analytics and learning create a seamless, reciprocal relationship between digital tools and the physical environment.
The future of work depends not just on technology but also on how intelligently your building uses data to improve the employee experience (EX), meet net-zero goals and ensure policy compliance.
When considering the design and management of a high-performing digital workplace, we must move beyond simple automation and focus on the critical interplays that truly define success.
The interplay of experience, wellbeing and technology
EX is at the heart of the digital workplace:
- AI-driven EX: AI-driven dynamic zoning elevates EX by shifting from static settings to a hyperpersonalized environment. Using machine learning, the system learns individual preferences (light, temperature, noise) and automatically adjusts local settings upon check-in, turning the office into a responsive environment that’s proactively tuned for focus, collaboration and wellbeing.
- Predictive wellbeing: A smart building acts as a silent “Chief Wellbeing Officer.” Predictive AI algorithms process real-time sensor data on air quality, carbon-dioxide concentration and noise pollution. Instead of simply reporting issues, they also initiate proactive microadjustments to the ventilation or lighting systems even before comfort levels drop, effectively mitigating environmental stressors and driving engagement.
The underpinning technology is IoT. Sensors and actuators collect granular data that feeds directly into employee-facing platforms, proving that the digital tools and the physical space are now inseparable.
The interplay of sustainability, policies and legislation
Smart buildings are vital instruments in meeting modern environmental and regulatory demands:
- AI-enabled net-zero goals: Energy efficiency starts with predictive analytics. Modern building energy-management systems use model predictive control to dynamically manage heating, ventilation and air-conditioning (HVAC) and lighting. This sophisticated form of AI not only predicts occupancy but also models future weather conditions and energy prices to find the lowest carbon-footprint operating path, resulting in potential energy savings of up to 20%. This is a demonstrable commitment to corporate environmental goals, which is crucial to any employer’s brand.
- Policy and the mandate for explainability: As AI takes on high-stakes tasks like energy compliance, the legal landscape demands explainable AI (XAI). Every automated decision — from a system prioritizing low-carbon energy to an alert for a potential equipment failure — must be auditable and comprehensible to human managers. The building becomes a transparent compliance engine, not a black box, ensuring that policies on resource allocation and safety are data-driven and fully verifiable.
The interplay of people and supporting technologies
While technology is the enabler, the “people element” is the ultimate beneficiary. The most sophisticated smart-building technology is useless if it doesn’t solve human problems:
- AI for community: To foster community and collaboration — a key pillar of the hybrid work challenge — the building must become an intelligent concierge. Modern AI-driven space management moves beyond simple desk-sharing. By analyzing anonymous interaction data and meeting patterns, AI can predict collaboration needs, dynamically allocate space and suggest optimal times and zones for teams to meet. This solves a major pain point of the hybrid office: “Why should I bother coming in if I can’t find my team?”
- Seamless adoption: Success is measured by adoption and AI-informed behavioral change. The technology should disappear; we achieve this by using AI to drive seamless experiences — from automatically adjusting light and sound for a scheduled meeting to proactively reserving the rightsized collaboration room. This personalization builds trust and increases use, leaving behind only a positive, friction-free experience.
Measuring maturity: The path to digital workplace excellence
An organization cannot effectively manage what it doesn’t measure. This brings us to the crucial need for a robust maturity model that assesses the depth of integration across employee experience, wellbeing, sustainability and supporting technologies.
The journey to an optimized state is the journey toward full digital-twin adoption. A digital twin, powered by AI and continuously fed by IoT data, is an intelligent core allowing managers to run “what if” scenarios for space planning, predict maintenance failures and model sustainability outcomes in real time, so that building operations are always maximized for EX, wellbeing and carbon goals. Ignoring the physical dimension is to build a digital workplace on a fundamentally incomplete foundation.
Takeaways: Your next steps on the path to an intelligent core
To accelerate your journey toward an optimized digital workplace, ask these three critical questions:
1. “Do our building systems support XAI for policy compliance?”
Action: Verify that your building management systems can provide auditable reasoning for automated decisions (such as shutting down heating and HVAC) or shifting energy sources. This is crucial for navigating emerging legislation such as the EU’s AI Act and internal sustainability policies.
2. “How are we using predictive data to drive wellbeing, not just efficiency?”
Action: Move beyond simply reporting air quality and temperature. Assess whether your system uses AI algorithms to predict and proactively mitigate environmental stressors (for example, automatically boosting ventilation before carbon-dioxide levels impact cognitive function).
3. “What’s our roadmap for implementing a digital twin?”
Action: Recognize that the optimized maturity state is defined by the ability to model and simulate outcomes. Ask how a digital twin, powered by AI, could enable your teams to run “what if” scenarios for space planning, retrofits and operational resilience, all before making costly physical changes.
How can NTT DATA help?
We provide advisory services for the digital workplace, including a maturity assessment for smart real estate such as buildings and campuses. The assessment examines the interactions between people, policies, technology and sustainability in a strategic context. We identify gaps in maturity by comparing a client’s current state with their desired future state along a practical timeline. This leads to a prioritized roadmap for transformation that details specific NTT DATA services and solutions to address gaps.