10 Things You Can Definitely Expect From The Future Of Healthcare AI

The steady cadence of a heart monitor. The anxious wait for test results. These define a patient's experience, but for healthcare professionals, they are also points of friction. Missed information, redundant diagnostics, or the struggle to make time for true connection... these burdens hinder the most skilled and compassionate providers.?

Artificial intelligence promises material changes on both sides of the stethoscope. By streamlining processes, pinpointing insights, and augmenting decision-making, AI won't just change how care is delivered – it will reshape the very experience of both giving and receiving that care.

We have written so much about various details of this revolution in the past period, so it was time to come up with a high-level overview of what we can certainly expect from AI in medicine. We have 10 predictions, coming from four distinct facets of the healthcare spectrum.?

The ultimate interface to AI

1) The future of large language models (LLMs) is multimodal

Healthcare isn't one-dimensional. Physicians synthesize information from conversations, scans, lab results, and a patient's gestures to reach a diagnosis. Until now, AI has largely worked in silos – analysing text, interpreting images, and so on. To use a simple analogy: current LLMs are like individual tools in a toolbox— a hammer is great for nails, a saw for wood, etc. But a good builder needs to use them in combination.?

Medicine demands this multifaceted approach. Multimodal AI is about giving the algorithm a whole toolbox, not just a single tool. The true revolution will come when AI models can mimic the clinician's multi-pronged approach. We already see the early stages of this with multimodal LLMs , and their impact will only deepen. Imagine an AI partner as multifaceted as the challenges it aims to solve.

2) Data annotators will be celebrated

Multimodal AI might usher in futuristic visions, but its foundation is decidedly unglamorous: meticulously labeled data. Think of every X-ray painstakingly annotated with diagnoses, medical conversations transcribed, and the subtle nuances of lab report values precisely defined. This work is the lifeblood of accurate AI , yet it often goes unnoticed and under-appreciated.

The path to reliably working medical AI is built with a hidden, but crucial workforce: data annotators . Their meticulous labeling of medical images, conversations, and test results is the unseen foundation upon which accurate AI models are built. In the rush towards futuristic visions, it's easy to overlook these essential contributors. It's time to recognize data annotators as vital players in the AI healthcare revolution, ensuring their work is valued and compensated. We must also create systems for recognition and career paths within the field, for without their expertise, even the most sophisticated algorithms will crumble.

AI's impact

3) AI will not replace physicians or make specialties vanish

Despite the breathless headlines, the fear that AI will replace doctors is very likely unfounded . While AI will undoubtedly change how physicians work, it won't eliminate the need for their expertise, judgement, and human connection.?

Instead of displacement, the future of healthcare lies in intelligent partnerships between humans and algorithms. AI will become a powerful tool, augmenting physicians' abilities and ultimately improving patient outcomes. Let's explore why this is a near certainty... While AI excels at pattern recognition and data analysis, it lacks the empathy essential for patient-centered care. Physicians, in contrast, use a non-linear approach, integrating intuition, experience, and a deep understanding of their patients' unique needs.?

Additionally, complex AI tools will always demand skilled practitioners to interpret their output and ensure responsible application. And as history consistently demonstrates, technological advancement creates new roles and opportunities rather than simply replacing existing ones.

4) AI will primarily take over repetitive and data-based tasks

AI's most immediate impact in healthcare won't be stealing doctors' jobs, but rather stealing away the drudgery. The repetitive, data-driven tasks that weigh down physicians – from analyzing scans to sifting through medical records – are prime targets for AI automation. This won't just save time; it will transform the very nature of medical practice as the human role shifts away from the mundane and toward tasks demanding creativity, connection, and complex problem-solving.

As research consistently shows, the best outcomes arise from intelligent human-machine collaboration. By taking on the analytical heavy lifting, AI will free physicians to focus on the art of medicine. This means more time for patient interaction, greater space for nuanced diagnoses, and the exploration of novel treatment strategies. While the fear of AI replacement is understandable, the reality is that doctors who embrace AI as a powerful tool stand to elevate both their profession and the care they provide.

5) AI will find unusual biomedical associations and biomarkers

AI is poised to become an invaluable tool for uncovering hidden patterns and connections in the vast landscape of medical data. Like a detective with superhuman perception, AI can spot subtle anomalies or correlations that elude even the most experienced human physicians. Race prediction from X-rays, or diabetes detection through voice analysis - these are just early examples of AI identifying biomarkers no human anticipated.

While such discoveries raise valid concerns about bias and explainability, they also signal a revolutionary shift in medical research. Imagine AI uncovering previously unseen risk factors for devastating diseases or pinpointing the subtle markers that predict which patients will best respond to specific therapies. These unusual associations aren't just AI curiosities; they challenge us to decipher the algorithm's logic and unlock new frontiers of medical understanding. Medical detective work will have a new aim: to understand how AI finds what it finds, ensuring these groundbreaking insights are used ethically and for the betterment of patient care.

Skills you will need

6) You will need a common language with AI to understand its progress - and it’s not coding

Contrary to popular belief, the language of AI isn't Python or Java. The true common tongue is anticipation. Understanding how AI algorithms approach problems, anticipate consequences, and learn from their mistakes is essential for doctors seeking to effectively collaborate with these systems.

Luckily, this doesn't require coding classes. Activities like chess, go, or even strategy-based video games (like StarCraft) cultivate the same anticipatory mindset . They immerse you in worlds where you must analyse complex scenarios, predict multiple moves ahead, and iteratively adapt based on an opponent's (or an algorithm's) actions. Physicians who approach AI with this gamer-like problem-solving mentality will be well-positioned to unlock its potential and guide its development in healthcare.

7) Prompt engineering is the number one tech skill for medical professionals in the generative AI era

If anticipation is the language of AI, then let’s see how you can improve your pronunciation - or to put it technically: learn prompt engineering.?

The AI revolution isn't just about technology – it's also about how we interact with it . In the era of generative AI, those who master the art of communication with these algorithms will have a distinct advantage. Prompt engineering, the skill of crafting effective prompts that guide AI models, will become an essential tool for physicians seeking to harness AI's potential in patient care.

Think of it like this: physicians already 'prompt' patients to gain the information needed for diagnosis. With AI, the skill evolves. Mastering prompt engineering will allow doctors to pinpoint the most accurate information, request tailored analyses, and ensure the AI's output aligns precisely with their patient's needs. Those who embrace this skillset will not only improve their efficiency but will also unlock the true promise of the human-AI partnership.

Challenges

8) We need proper guidelines about health equity and fighting bias

Bias and lack of equity are among the most urgent challenges as AI transforms healthcare. The good news: we're already seeing efforts , from technical toolkits to research frameworks, to tackle these issues head-on. However, translating these solutions into widespread practice requires a foundation of clear, actionable guidelines. Expect a surge in standards focused on data fairness, algorithmic transparency, and the ongoing monitoring of AI systems in real-world settings.

These guidelines won't just protect patients; they'll be essential for building trust and broad acceptance of AI in medicine. Doctors seeking to uphold the principle of 'do no harm' in the AI era will need fluency in these equity standards .

9) Adaptive AI and generative AI will get new regulatory categories

Generative and adaptive AI pose a thrilling, yet unprecedented challenge for regulatory bodies . Unlike static medical devices or software, these algorithms evolve and continuously learn. This is a brand new challenge: the likes of the FDA never before had to figure out a suitable framework for something that might be different by tomorrow.?

This requires a regulatory approach that balances innovation with patient safety. We expect the emergence of entirely new categories and flexible frameworks specifically designed to govern these dynamic AI systems.

Healthcare professionals will need to become active participants in shaping these new regulatory standards. Understanding the unique challenges of generative and adaptive AI, as well as engaging in the ethical considerations surrounding their use, will be vital. Only by working in partnership with regulators can healthcare providers ensure a future where AI innovation flourishes while patient well-being remains the guiding principle.

10) Medicine and healthcare will struggle to adapt and filter deepfakes

As deepfake technology becomes more sophisticated, medicine faces a unique vulnerability. Patients could encounter deepfake doctors , convincingly mimicking their trusted healthcare providers. Fabricated patient records or misleading research data have the potential to disrupt care and erode trust. Healthcare institutions will struggle to adapt, requiring both healthcare personnel and patients to be educated on the potential threats of deepfakes. Developing robust methods for identifying and combating deepfakes will become a critical priority.

This is where medical professionals need to be vigilant. We must question the authenticity of information, especially AI-generated content, to foster a culture of skepticism within the field. The trust patients place in healthcare hinges on our ability to discern fact from fiction in an era where the lines are increasingly blurred. Will you have secret passwords with your patients? While it's too early to predict specific solutions, staying ahead of the deepfake curve is essential to protect both our patients and the integrity of medical knowledge.

The AI healthcare revolution won't unfold in isolation

The future of AI in healthcare is undeniably complex, but it brims with transformative potential. From unlocking hidden biomarkers to streamlining administrative burdens, AI will improve patient care and redefine the role of physicians. However, this revolution won't unfold on its own. It requires collaboration between physicians, technologists, regulators, and patients. Healthcare professionals need to embrace this change and use their ethical compass to shape the future of medicine for the better.

While AI promises to augment our abilities, it's essential to remember that healthcare remains a fundamentally human endeavor. The most sophisticated algorithm can never replace empathy, intuition, or the healing power of the patient-doctor bond. Technology can serve as a powerful tool, empowering us to provide better, more compassionate care for all.