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The Role of Generative AI in Healthcare

Artificial intelligence (AI) is transforming the healthcare industry in various ways, from improving diagnosis and treatment to enhancing patient experience and reducing costs. One of the most promising and innovative branches of AI is generative AI. 

Generative AI uses deep learning models, such as generative adversarial networks (GANs) or large language models (LLMs), to learn from extensive data and produce realistic and diverse outputs.

According to a report by Market.us, the global Gen-AI in healthcare market size was valued at USD 1.2 billion in 2022 and is expected to reach USD 8.9 billion by 2032, growing at a CAGR of 22.7% during the forecast period. 

Given the broad focus, this emerging technology has enormous potential to revolutionize healthcare in unprecedented ways, but it also poses some challenges and risks that need to be addressed.

What are the applications of generative AI in healthcare?

Generative AI has many potential applications in healthcare, such as:

• Data augmentation: Firms can create synthetic data that can augment the existing data and improve the performance and accuracy of other AI models. For example, creating synthetic medical images that can help train diagnostic or predictive models with more data and diversity. 

American healthcare company, CloudMedX is a computing platform that improves patient outcomes using predictive analytics. It uses AI to collect data and build holistic pictures of individuals and communities. Its single, unified data platform has operational, clinical, and financial functions, meaning healthcare providers can find everything they need in one place. 

The company’s predictive healthcare models can predict disease progression and determine the likelihoods that patients may have complications by processing medical data and providing risk assessment scores. 

• Data privacy: Using generative AI, healthcare companies can create anonymized data to protect patients’ and providers’ privacy and security. For example, synthetic patient records can be used for research or analysis without revealing actual patients’ identities or sensitive information.

• Data generation: We can create new data or content that can provide insights or solutions for healthcare problems. For example, USA-based startup Persado uses generative AI to create personalized and persuasive content for healthcare communication and engagement. Their digital solutions, Persad PerScribed and Persado Motivation AI Platform have helped healthcare companies, insurers, and retail clinics conduct effective campaigns. 

• Data enhancement: Generative AI can enhance the existing data or content by adding more details or quality. For example, the tech can help respond to patient queries better. Google DeepMind has developed MedPaLM, a large language model (LLM) trained on medical datasets that can respond to healthcare queries. 

Nuance Communications, a technology provider of advanced conversational AI for ambient clinical documentation and decision support through voice biometrics; and specialized ambient sensing hardware, leverages Open AI’s Chat GPT to enhance customer responses and manage administrative tasks. 

Data synthesis: Generative AI can synthesize different data or content types to create a comprehensive and coherent output. AI-based firm Zebra Medical Vision has developed more than 11 algorithms to help medical professionals detect diseases better. Their HealthMammo tool is trained on over 350,000 mammogram reports and detects cancer with a 92% success rate compared to 87% among radiologists.

What are the challenges and risks of generative AI in healthcare?

Generative AI is still an evolving technology that faces some challenges and risks, such as:

• Quality and reliability: Generative AI may produce inaccurate or unrealistic outputs that may mislead or harm users. For example, it may generate false medical information that may affect diagnosis or treatment decisions or generate fake medical images that may violate ethical standards.

• Regulation and governance: There may be a lack of clear rules or guidelines for its development and use in healthcare. For example, there may be questions about accountability, transparency, explainability, fairness, and safety in healthcare settings.

• Ethics and trust: Given the lack of human touch, generative AI may pose ethical and social issues that may affect the trust and acceptance of users. The digital products using it creates may generate harmful or offensive content that affects public health in a worst-case scenario.

Conclusion

Generative AI is a rapidly evolving ecosystem of tools that holds enormous promise for healthcare. It can address some healthcare challenges, such as pandemics, chronic diseases, staff shortages, and administrative burdens. However, the technology also comes with its own challenges and risks that must be carefully considered and managed. Therefore, it is essential to develop trustworthy and responsible generative AI systems that can benefit healthcare without compromising its quality and integrity.

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Empowering Frontline Healthcare Sales Teams with Mobile-First Tools

In healthcare, field sales is more than just hitting quotas—it’s about navigating a complex stakeholder ecosystem that spans hospitals, clinics, diagnostics labs, and pharmacies. Reps are expected to juggle compliance, education, and relationship-building—all on the move.

But, traditional systems can’t keep up. 

Only 28% of a rep’s time is spent selling; the rest is lost to administrative tasks, CRM updates, and fragmented workflows.

Salesforce, State of Sales 2024

This is where mobile-first sales apps in healthcare are changing the game—empowering sales teams to work smarter, faster, and more compliantly.

The Real Challenges in Traditional Field Sales

Despite their scale, many healthcare sales teams still rely on outdated tools that drag down performance:

  • Paper-based reporting: Slows down data consolidation and misses real-time insights
  • Siloed CRMs: Fragmented systems lead to broken workflows

According to a study by HubSpot, 32% of reps spend at least an hour per day just entering data into CRMs.

  • Managing Visits: Visits require planning, which may involve a lot of stress since doctors have a busy schedule, making it difficult for sales reps to meet them.
  • Inconsistent feedback loops: Managers struggle to coach and support reps effectively
  • Compliance gaps: Manual processes are audit-heavy and unreliable

These issues don’t just affect productivity—they erode trust, delay decisions, and increase revenue leakage.

What a Mobile-First Sales App in Healthcare Should Deliver

According to Deloitte’s 2025 Global Healthcare Executive Outlook, organizations are prioritizing digital tools to reduce burnout, drive efficiency, and enable real-time collaboration. A mobile-first sales app in healthcare is a critical part of this shift—especially for hybrid field teams dealing with fragmented systems and growing compliance demands.

Core Features of a Mobile-First Sales App in Healthcare

1. Smart Visit Planning & Route Optimization

Field reps can plan high-impact visits, reduce travel time, and log interactions efficiently. Geo-tagged entries ensure field activity transparency.

2. In-App KYC & E-Detailing

According to Viseven, over 60% of HCPs prefer on-demand digital content over live rep interactions, and self-detailing can increase engagement up to 3x compared to traditional methods.
By enabling self-detailing within the mobile app, reps can deliver compliance-approved content, enable interactive, personalized detailing during or after HCP visits, and give HCPs control over when and how they engage.

3. Real-Time Escalation & Commission Tracking

Track escalation tickets and incentive eligibility on the go, reducing back-and-forth and improving rep satisfaction.

4. Centralized Knowledge Hub

Push product updates, training videos, and compliance checklists—directly to reps’ devices. Maintain alignment across distributed teams. 

5. Live Dashboards for Performance Tracking

Sales leaders can view territory-wise performance, rep productivity, and engagement trends instantly, enabling proactive decision-making.

Case in Point: Digitizing Sales for a Leading Pharma Firm

Mantra Labs partnered with a top Indian pharma firm to streamline pharmacy workflows inside their ecosystem. 

The Challenge:

  • Pharmacists were struggling with operational inefficiencies that directly impacted patient care and satisfaction. 
  • Delays in prescription fulfillment were becoming increasingly common due to a lack of real-time inventory visibility and manual processing bottlenecks. 
  • Critical stock-out alerts were either missed or delayed, leading to unavailability of essential medicines when needed. 
  • Additionally, communication gaps between pharmacists and prescribing doctors led to frequent clarifications, rework, and slow turnaround times—affecting both speed and accuracy in dispensing medication. 

These challenges not only disrupted the pharmacy workflow but also created a ripple effect across the wider care delivery ecosystem.

Our Solution:

We designed a custom digital pharmacy module with:

  • Inventory Management: Centralized tracking of sales, purchases, returns, and expiry alerts
  • Revenue Snapshot: Real-time tracking of dues, payments, and cash flow
  • ShortBook Dashboard: Stock views by medicine, distributor, and manufacturer
  • Smart Reporting: Instant downloadable reports for accounts, stock, and sales

Business Impact:

  • 2x faster prescription fulfillment, reducing wait times and improving patient experience
  • 27% reduction in stock-out incidents through real-time alerts and inventory visibility
  • 81% reduction in manual errors, thanks to automation and real-time dashboards
  • Streamlined doctor-pharmacy coordination, leading to fewer clarifications and faster dispensing

Integration Is Key

A mobile-first sales app in healthcare is as strong as the ecosystem it fits into. Mantra Labs ensures seamless integration with:

  • CRM systems for lead and pipeline tracking
  • HRMS for leave, attendance, and performance sync
  • LMS to deliver ongoing training
  • Product Catalogs to support detailing and onboarding

Ready to Empower Your Sales Teams?

From lead capture to conversion, Mantra Labs helps you automate, streamline, and accelerate every step of the sales journey. 

Whether you’re managing field agents, handling complex product configurations, or tracking customer interactions — we bring the tech & domain expertise to cut manual effort and boost productivity.

Let’s simplify your sales workflows. Book a quick call.

Further Reading: How Smarter Sales Apps Are Reinventing the Frontlines of Insurance Distribution

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