This is the total amount that industries across the globe can expect to earn by 2030—all thanks to Artificial Intelligence (AI). This technology will be the key player in the transformation and growth of all kinds of businesses1.
Artificial Intelligence is powered by live data patterns and algorithms. It enables machines to have human-like intelligence and perform tasks at rapid speed accurately. For example, computer vision is a form of AI technology that enables a machine to identify information visually like humans. Similarly, Natural Language Processing (NLP) enables machines to interact with humans by processing and understanding human speech and language data.
Healthcare companies are one of the most exciting industries that leverage AI, even before the pandemic, but its adoption has accelerated rapidly due to increasing demand for high-quality medical services. Automating manual tasks such as patient intake forms and other administrative jobs allows medical care professionals and providers to focus on higher priority work and operate more efficiently. And with patients’ big data powering this AI, doctors can diagnose diseases quicker, easier, and more accurately2.
Data Science and Machine learning (ML) has also helped accelerate research for COVID-19 vaccines, surgical techniques, and groundbreaking medical research.
Currently, the market demand for AI in healthcare is increasing. With this, the global AI revenue in healthcare is expected to reach $27.2 billion by 20253. Currently, 90% of hospitals in the United States have adopted AI in some form—higher than the 53% record during the third quarter of 2019.
Given this acceleration, will AI stay in healthcare post-pandemic?
COVID-19 has taught us to reevaluate the healthcare system, and now, digital healthcare technology is being heavily used by the Center for Disease Control (CDC) for their chatbot and contact tracing efforts. According to a recent Intel survey, the number of healthcare companies that will adopt AI will nearly double post-pandemic inception. And while AI cannot substitute the human touch of healthcare professionals, it could augment their expertise in treating high-risk patients, diagnostic analysis, and screening. As AI has proven itself effective in helping the industry move faster, expect the technology to stay even after the world survives Covid-194.
According to AI experts Fei-Fei Li and Andrew Ng of Stanford University, while AI is still in the developing phase, taking a “human-centered approach” is essential to boost AI in healthcare. Some of the key factors in the successful adoption of AI solutions are integrating the human element, and understanding the needs of patients and healthcare professionals alike5.
The healthcare industry, in particular, has been facing several issues, such as overwhelming workload for both healthcare professionals and providers, unnecessary hospital visits, and inefficient processes. While many healthcare companies have embraced digitization to address these issues, healthcare professionals and providers are still facing new challenges ahead. For instance, the overwhelming volume of patient data poses threats to the industry. Moreover, data privacy, data security, data leakage, privacy compliance, and transparency are some of the challenges found in AI applications, let alone the performance if not trained well using high-quality volume of data6 7. These challenges must be addressed in order to outsource healthcare solutions in AI development.
Data sensitivity is a top priority for healthcare companies and it should be for your partners as well. We strictly follow industry security standards such as PCI, ISO, and SOC2 certifications. We are also compliant with Health Insurance Portability and Accountability Act (HIPAA), General Data Protection Regulation (GDPR), and we utilize the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF).
As a partner of leading healthcare companies, we recognize the sensitivity and rigor of data compliance and intelligence behind innovative medical technologies. Our methods enable technology disruptors to accelerate their machine learning efforts, improve model performance, derive meaningful data insights, and minimize risks. By leveraging machine learning in our labeling, quality assurance (QA), and model validation workflows, we can bring greater efficiency and accelerate our client’s various initiatives. We leverage machine learning annotation and management platforms in assisting our clients.
More than the fancy tech and operations training artificial intelligence, we have incredible talent—a key differentiator. Our Team Members are data experts who understand the context behind the data and provide feedback to help prioritize efforts and solve challenges in building high-performing machine learning models. Our clients can build smarter technologies faster because of who powers their AI. Among the world’s AI data labeling providers, we’ve set the bar high through our unparalleled Employee Net Promoter Score (eNPS) of 72 while our Client Net Promoter Score (cNPS) is 75 as of 2020.
In healthcare, AI can definitely do some amazing things—but at the end of the day, nothing heals like a human touch.
To know more about the services, visit our AI Operations solutions.