AI in healthcare: A partner, not a replacement for doctors

2026-03-04 - 00:47

By Juliet Umeh For years, many people have worried about the rise of Artificial Intelligence, AI, in healthcare. A common fear has been that machines might one day replace doctors. But across Africa, a different story is beginning to take shape. Instead of taking over, AI is showing that it can support doctors, helping them work faster, make better decisions, and improve patient care. Rather than replacing medincal professionals, AI is becoming a helpful assitant in strengthening the continent’s growing health systems. At a recent webinar organised by Newmark on “AI in Healthcare: Opportunities and Challenges,” experts stressed that AI’s growing presence in hospitals and national health systems is designed to strengthen clinical decision-making, not sideline medical professionals. Co-Founder of RX Health Info System, Daniel Marfo, recalled how unthinkable such a conversation would have been just five years ago. “Healthcare is built on protocols, training and years of experience. So naturally, there was scepticism,” he said. “But what we are seeing now is that AI is sharpening clinical focus, not replacing it.” He said: “In many hospitals today, AI tools are embedded within Electronic Medical Records, EMRs. As doctors document patient symptoms and history, AI assistants can suggest possible diagnoses, highlight patterns and prompt additional questions that may otherwise be overlooked in a busy clinic. “AI helps doctors process large volumes of information within limited consultation time,” Marfo explained, stating that, “It does not make decisions, it supports the decision-maker.” This support is particularly valuable in high-pressure environments where doctors face overwhelming patient loads and limited resources. He stated: “One of AI’s most significant contributions lies in medical imaging. AI-powered systems can analyse X-rays, CT scans and MRIs with remarkable speed, flagging abnormalities that require further attention. In many African countries where radiologists are scarce, this capability can reduce waiting times and accelerate treatment decisions. “In some facilities, patients wait days because a specialist is unavailable. AI tools are helping to bridge that gap by offering preliminary insights that clinicians can act on quickly,” Marfo noted. AI does not issue definitive diagnoses independently. Rather, it functions as a second set of eyes, enhancing accuracy and efficiency. According to Marfo, “Beyond clinical interpretation, AI is easing administrative pressures that often drain healthcare professionals’ time and energy. “From automated medical transcription to intelligent claims-processing systems in health insurance, AI is reducing paperwork, cutting delays and allowing doctors to devote more time to patient care instead of documentation. “For clinicians, this shift can translate into shorter waiting times and improved patient experience.” Building smarter, more resilient systems Also speaking, Founder, Aduru Analytics/PharmaD, Dr. Afriye Bempah underscored that AI’s broader value lies in strengthening system resilience. He said: “AI-driven surveillance systems are being developed to detect disease outbreaks earlier by analysing patterns in health data. By converting raw data into actionable insights quickly, these systems give healthcare professionals and policymakers more time to respond effectively. “ However, Bempah emphasised that technology must be implemented responsibly to achieve these outcomes. The limits and the guardrails Experts acknowledged that AI is not without limitations. Issues such as data privacy, algorithmic bias and fragmented health records remain significant challenges. “In healthcare, mistakes affect lives,” Bempah cautioned. “Patient privacy and ethical use must remain central.” Another challenge lies in perception. Some clinicians remain wary of AI tools, while some patients, armed with chatbot-generated information, may overestimate AI’s capabilities. The key, speakers agreed, is positioning AI clearly as a supportive tool, one that augments professional expertise rather than competes with it. Communication and ethical safeguards Also speaking, the Chief Executive Officer of Newmark Group, Gilbert Manirskiza, urged communication professionals in the healthcare sector to adopt stronger safeguards around data privacy, bias mitigation and ethical disclosure as AI becomes more embedded in public messaging. Describing the ethical dimensions of AI communication as “critical and urgent,” he warned that misinformation or misuse of data in healthcare could have life-altering consequences. “One of the biggest challenges communicators must address is data privacy,” he said. “If patient data is being used in AI systems that are not properly governed or accountable, that becomes an ethical problem. Communication teams must openly and authentically share what is being done to protect that data.” He stressed that transparency in how health data is processed, stored and safeguarded must form part of public messaging, particularly as AI-powered systems are integrated into diagnostics, data management and information-sharing platforms. Tackling bias and ensuring disclosure Manirskiza highlighted concerns around algorithmic bias, noting that many large language models are trained predominantly on non-African populations, cultures and geographies. “Bias is a structurally significant issue,” he said. “As communicators, we must be sensitive to the fact that many AI systems are trained on datasets that underrepresent African contexts.” He advocated for the development of locally trained, custom-built AI systems by governments and institutions to improve cultural and contextual accuracy. On disclosure, he argued that the public has a right to know when content has been substantially generated or shaped by AI, particularly in healthcare communications. “In this sector, disclosure may need to become a standard ethical consideration,” he noted.