When it comes to AI in healthcare, the potential is boundless, unfathomable, and likely to revolutionize care on many fronts. But just because new applications for AI in healthcare are proliferating at breakneck speed, it doesn’t mean that the industry can adopt them at the same pace.
Tech companies offering AI-driven healthcare solutions already know how resistant the industry can be toward change – and how the emergent market is already overwhelming with products and claims. The best way to stand out is to understand that resistance and to show prospects exactly why your AI product is worth the hassle of creating massive institutional change.
Why Healthcare Companies Are Notoriously Slow to Change
Even the most progressive and agile healthcare companies have to confront forces outside of their control when implementing new tech, leading them to exhibit hesitancy toward adopting breakthrough products or services.
Regulatory Requirements
Companies in the healthcare space are held to an array of regulatory requirements, and AI is a transformative enough tool that new or revised regulations will crop up in the near future. Healthcare decision-makers are likely to have an eye on the horizon and want to understand how new AI tools will affect their compliance efforts.
Liability and Ethical Concerns
AI platforms in healthcare touch a unique nerve that many other industries don't: the potential for loss of human life or health. This is an ethical concern as well as a liability issue. Who is responsible if an AI makes a mistake that harms a patient? What happens if a patient recieves sub-par care by a faulty or biased AI? Will physicians be held liable for failing to critically review AI recommendations?
Lack of Clinical Validation
Many healthcare providers are also concerned about clinical validation, which can be difficult to prove for new products. Clinical validation ensures that a new product meets the necessary efficacy, safety, and regulatory standards before being introduced into the healthcare system.
Healthcare organizations want as much certainty as possible that a product will perform under the day-to-day pressure present in healthcare settings and that AI outputs align with established best practices in medicine.
Data Access Limitations
While AI solutions are becoming more powerful, they won’t reach their full potential until the data equation is solved. Insufficient breadth and depth of data leads to bias and other poor clinical outcomes, but privacy laws limit how patient data can be used. Healthcare companies are understandably cautious.
Personnel and Training Challenges
Healthcare providers may lack in-house expertise in AI technologies, and hiring or training staff to implement and manage AI systems can be a significant challenge in an industry that’s notoriously understaffed and overworked.
Healthcare workers are also not immune to concerns about AI replacing them in care settings. Healthcare professionals may be resistant to adopting new technologies when they're concerned that AI will replace or devalue their roles.
Cost and ROI Uncertainty
All of these challenges cast the cost and ROI of implementing complex AI platforms in a harsher light. Hospitals must weigh the benefits of AI against the upfront and ongoing costs, and demonstrating a clear return on investment (ROI) can be challenging.
These barriers all make implementing AI solutions in healthcare more challenging than in other, less regulated, faster-moving industries, which translates into additional challenges for SaaS companies marketing their products to the healthcare industry.
Positioning + Messaging Around AI Will Separate Hyped Products From Valuable Ones
To cut through the noise around AI and inspire prospects to create change, AI healthcare marketers must focus marketing efforts on demonstrating the value created by their product or service — not the hype around AI itself.
The key to success lies in understanding that AI is not a value proposition on its own. Instead, SaaS marketers must establish a strong connection between their product and the front-line challenges faced by healthcare businesses. They have to understand and make clear how integrating AI enhances the value proposition of the product to clear the hurdles inherent to the healthcare industry.
The most important manifestation of this concept is through marketing and sales messaging. Whether it's on the front page of the website, articles posted to the company blog, or pitch decks utilized by salespeople, messaging around AI products must clearly demonstrate how they address business challenges and make their buyers' aspirations a reality.
What Does Engaging Messaging Around AI in Healthcare Look Like?
To better understand what effective messaging around AI for healthcare companies looks like in action, let's consider the fictional AI startup MediPlanner.
Product: MediPlanner sells an AI platform that uses historical patient data to create tailored treatment plans for individual patients.
Target Buyers: High-traffic healthcare clinics in low-income areas.
Buyer Challenges:
- Lower-priced services mean they often struggle to balance providing quality care with limited time and resources.
- High staff and provider turnover leaves providers tasked with creating treatment plans for patients whose history they don't know very well.
Buyer Aspirations: These clinics want to continue serving a high volume of patients without sacrificing the quality of their care.
Marketers who don't fully understand their buyer's aspirations might develop copy like, "Our AI platform transforms treatment plan creation." At first blush, this may sound compelling, but when you consider the challenges that healthcare companies face implementing AI solutions, it's too product-focused to be appealing to those buyers.
This messaging is likely to leave buyers wondering: what does that transformation look like? What part does AI play? How much work is required from front-line staff to make it happen? And will that transformation actually help us meet our aspirations?
On the other hand, marketers with a deep understanding of their buyers and the industry they operate in might develop something more like, "Our product provides in-depth insights and informed suggestions that enable providers to create tailored treatment plans for a high volume of patients."
While this copy still relays what their AI product does, it frames the product using their buyers' aspirations of balancing patient care with their providers' workloads.
Translate Value Propositions into Concrete Results
While the hype around AI is picking up speed and new tools are rapidly permeating other industries, healthcare decision-makers will be more measured and hesitant than their counterparts. For AI SaaS companies navigating the dynamic landscape of healthcare and technology, it's critical to focus on creating tangible value and addressing real-world challenges rather than getting lost in hype.
Remember, at the end of the day, it's not about AI — it's about solving problems and improving lives.
