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Accenture Technology Vision 2025 and Healthcare
AI: A Declaration of Autonomy
10-MINUTE READ
March 26, 2025
The healthcare sector is entering the next chapter of profound transformation, driven by the rapid evolution of AI technology and its potential to reinvent access, experience and outcomes. At the center of this transformation is the proliferation of accessible and ever-present AI as described in our recently published Technology Vision 2025.
At the core of this tech revolution in healthcare is the unchanging importance of trust.
81%
of healthcare executives agree they need to prioritize a trust strategy in parallel with their technology strategy.
"Realizing this vision requires more than just organizational adoption of new technologies; it demands a holistic approach that prioritizes building trust between humans and machines, and relentlessly making sure the technology abides to ethical, clinical, and humane standards."
The report identifies pivotal cross-industry technology trends that are influential in shaping the future. These four trends—The Binary Big Bang, Your Face in the Future, When LLMs Get Their Bodies, and The New Learning Loop—when looked at through the lens of healthcare, offer foresight to create a more connected, patient-centered, and efficient healthcare system.
To explore what the four trends mean for health see below. To dive deeper read the full blog here The Future, Here.
The binary big bang
The Binary Big Bang has transformed healthcare by making it easier and more cost-effective to connect, access, and analyze medical data. AI and agentic architectures are turning traditional systems into fully digitized, integrated networks that enhance patient care and operational efficiency.
- Digitization streamlines information flow, fostering collaboration and informed decision-making.
- Real-time data sharing improves patient transitions, reduces redundancies, and ensures continuity of care.
- Predictive analytics use data to anticipate needs, optimize resources, and improve outcomes.
Agentic Architectures centralize functions previously managed by complex systems or overburdened professionals. Digital agents interact with both legacy and new systems, aligning transactions and enhancing care delivery.
In a future emergency department, digital agents would coordinate treatment from the moment a patient arrives via autonomous ambulance. They analyze health data, cross-reference medical history, and communicate with imaging systems and specialists. Upon arrival, agents assign the patient to a treatment bay, prioritize resources, retrieve critical EHR information, monitor vitals, and suggest interventions.
The Binary Big Bang is the foundation for a connected, data-driven, and patient-focused healthcare system.
Read the full blog by Brian Kalis, Cassandra Lea, and Andy Truscott: The Binary Big Bang
Your face, in the future
Healthcare is a personal experience, often involving interactions with a diverse group of professionals. Technology, particularly AI and digital humans, can unify and enhance these interactions. digital humans, powered by agentic architecture, provide consistent, error-free, and 24/7 support, tailored to each patient's needs. They can assist with tasks like policy explanations, claim filings, and personalized health recommendations.
Biometric technologies, such as facial recognition and pulse detection, can further personalize and secure healthcare through;
- contactless check-ins,
- immediate access to medical records, and real-time monitoring,
- improved patient experiences
- reduced administrative burdens.
However, ensuring the secure and transparent handling of biometric data is crucial to building patient trust.
Read the full blog by Brian Kalis, Cassandra Lea, and Andy Truscott: YOUR FACE, IN THE FUTURE
When LLMS get their bodies
The integration of large language models (LLMs) with physical embodiments like robots and digital humans marks a significant advancement in healthcare. This convergence allows machines to understand and interact with complex healthcare environments, from hospitals to homes, offering services from health education to emotional support.
Robotic systems
Today
either human-operated or programmed for specific tasks
Yesterday
use LLMs and Vision Language Models (VLMs) to comprehend and adapt to their surroundings.
They can follow natural language instructions, making them accessible and versatile partners for both patients and healthcare staff. Embodied AI assistants can provide real-time feedback and advice to healthcare professionals, whether they are in the same room or miles away.
In underserved communities, these robots can bridge access gaps by handling complex tasks and learning new capabilities over time. They can also support elderly or chronically ill patients, reducing isolation and promoting well-being.
However, building trust is crucial. This involves ensuring patient privacy, data security, and transparent operations, as well as maintaining human oversight. Continuous testing and clinically approved guidelines are essential to ensure these tools enhance the patient experience.
Ultimately, the integration of LLMs into healthcare is not just a technological leap but a step toward more empathetic care.
Read the full blog by Brian Kalis, Cassandra Lea, and Andy Truscott: WHEN LLMs GET THEIR BODIES
The new learning loop
The New Learning Loop harnesses real-time data and feedback to fuel constant learning, adaptation, and immediate improvement—for both AI systems and the humans interacting with them. For the first time in healthcare's history, we have technology powerful and accessible enough to give everyone capabilities they don't personally possess.
Intelligent agents learn from the experiences of patients and providers, tailoring care to individual needs and fostering innovation and compassion. Healthcare professionals contribute to a cycle of continuous learning, identifying new best practices that improve patient outcomes and staff satisfaction. Recognizing this, 60% of healthcare leaders plan to upskill their workforce in generative AI tools within the next three years. Success involves not just training but also preserving the human touch that makes healthcare meaningful.
The New Learning Loop, while transformative, operates within established clinical regulation, legislation, and licensing standards to ensure patient safety and ethical practice. Healthcare organizations must adhere to strict guidelines from bodies like the FDA, AHA, and medical boards, ensuring patient data protection, clinical validation of AI decisions, and rigorous technology testing before deployment. This alignment with clinical oversight maintains trust and accountability
The New Learning Loop is not simply about keeping pace with technological change; it is about leading it—anticipating innovation and using it as a catalyst to deliver better, more effective care.
Read the full blog by Brian Kalis, Cassandra Lea, and Andy Truscott: THE NEW LEARNING LOOP
Conclusion: Building a future-ready healthcare system
Healthcare stands at a watershed moment of AI-driven reinvention. The trends outlined in Accenture's Tech Vision 2025 reveal how AI is transitioning from an enabler of automation to an autonomous partner in healthcare delivery and financing.
4 Key areas of focus with:
- Build your organization's cognitive digital brain: As AI becomes more generalized and autonomous, healthcare organizations must develop a comprehensive digital core that combines knowledge graphs, fine-tuned models, orchestrating agents, and enterprise-grade architecture. This cognitive digital brain will become your central nervous system for decision-making and continuous learning, enabling everything from improved clinical workflows, administrative operations and personalized healthcare consumer experiences.
- Empower your workforce to lead the AI transformation: Success demands more than just reskilling - it requires letting your healthcare professionals lead the way in AI adoption. When your workforce feels ownership over AI implementation, they naturally discover innovative applications that enhance patient care and financing and streamline operations. Healthcare leaders will need to set and guide a vision for how to reinvent work, reshape the workforce and prepare workers for a gen AI world, while building a resilient culture to navigate continuous waves of change.
- Develop distinctive, trustworthy AI personalities: As AI becomes healthcare's next major channel, generic interactions risk deepening the engagement crisis. Our research shows that patients who trust their healthcare providers are 6x more likely to stay with them. Organizations must design AI personalities that authentically reflect their values and care philosophy while maintaining the highest standards of ethics, safety, and privacy.
- Prepare for the physical-digital convergence: The emergence of foundation models in robotics, combined with advances in contextual understanding and natural communication, is expanding the potential for AI-powered automation in healthcare settings. From patient rooms to homes, these systems will require new approaches to data governance and security that enable safe human-machine collaboration while protecting patient privacy.
We stand at the threshold of healthcare's most significant technological transformation. Success will require more than just adopting new technologies - it demands a holistic approach that builds trust between humans and machines while ensuring improving healthcare access, experience and outcomes.
Read the full blog by Brian Kalis, Cassandra Lea, and Andy Truscott: BUILDING A FUTURE-READY HEALTHCARE SYSTEM