By Santosh Rao, NetApp
Artificial intelligence (AI) initiatives are supposed to enable us to reinvent how we do business, and, one day, transform society at large. However, the truth is that most organizations are still barely scratching the surface of AI’s potential. The biggest barrier to the success of AI continues to be an inability for many organizations to take advantage of the data they collect. Data is the lifeblood of AI; yet, according to an HBR survey, 69 percent of companies have not yet created a data-driven organization, and 52 percent aren’t even treating data as a business asset.
The bottom line is most companies haven’t figured out how to break down their data silos and gain insight across all their data. To innovate, they need data that is more accessible to new applications and workflows. They need a multi-cloud environment that is as agile, flexible, and expansive as their data is.
One industry is taking the lead on leveraging Big Data to make AI work and is blazing a trail that others can follow. An IDC-Seagate study found that the healthcare “datasphere” is one of the fastest growing—with a 36 percent Compound Annual Growth Rate (CAGR) from 2018 to 2025—due to advancements in healthcare analytics and increasing reliance on high-resolution MRIs and other image and video-related technology. Given this influx, it’s no surprise that many healthcare organizations are hard at work figuring out how to put all this data to good use, creating pools of knowledge that physicians and data scientists can access for better insights, better decisions and a better understanding of how to combat and prevent disease.
For a healthcare industry inundated with information, a data fabric can help organizations open the door to new possibilities. This data management strategy offers a way of connecting structured and unstructured data across multiple clouds and on-premises systems – keeping all the data necessary for a strong AI strategy accessible and digestible. WuXi NextCode, for example, is using a data fabric to sequence one million genomes in parallel. Once sequenced, the company uses an AI-enabled toolset to analyze all the massive amounts of genomic and clinical data, ultimately enabling practitioners to make life-saving decisions more quickly. On the other hand, Healthix is leveraging its Big Data management technology and cloud providers to provide patients with secure access to their personal information from anywhere in the world. Healthix also gathers Big Data for AI-sourced predictive analytics, allowing practitioners to calculate when and how a patient may become ill. Finally, Cambridge Consultants harnessed the power of AI to create BacillAi™ and address global health challenges around tuberculosis – offering a standard, low-cost hardware that improves treatment monitoring of the disease in the developing world where medical resources are in short supply.
All three of these healthcare companies, and countless more like them, are leaning into the era of AI – where analytics can save lives. This range of diverse, impressive, and critically important use cases prove that the applications of AI can be limitless. However, there is always a core commonality: a willingness to transform infrastructure to support these new ventures, often building a data fabric, supporting multi-cloud environments and breaking down data silos.
While healthcare is undoubtedly paving the way, all industries can benefit from leaning into AI, when done properly. They just need to follow five core steps to achieving real results with AI:
- Decide to act.
The growing prevalence of AI interest across industries means that companies need to recognize the need for AI and act on it to stay competitive. AI can unveil growth opportunities across industries through new interactions with customers, new products and new sales models. All this drives top-line growth. The reality of AI is here. Admitting that is the first, and potentially most crucial, step.
- Find the right software/code for your business.
Each business is different. So, while AI, at some scale, can be for everyone, finding the right software or the right code to achieve what you want is necessary. Prioritize what your business values most and determine goals before you begin exploring AI capabilities.
- Build on the right infrastructure.
Ignoring the power of data and how it can transform your business is far riskier than beginning the process and iterating on AI projects without proper infrastructure. If data is the lifeblood of AI, then before a business can begin its journey, it must have the necessary data prepared to be integrated into a data pipeline that can carry it from edge to core to cloud. This is where a data fabric comes in.
- Commit to the right implementation.
Most businesses begin their AI journey in the cloud because it is more flexible. Then as the new system evolves, with the right partners, it can be easily scaled across a hybrid multi-cloud. Partnering with a team who can help re-architect data as necessary and help achieve the utility and elasticity of the cloud with the deterministic performance of on-premises infrastructure is just as important as having the right AI technology.
- Take the time to conduct the right training
A business must understand, right off the bat, the difference between what they want to do and what they can do and proactively take steps to ensure they close that gap. Outsourcing the project, hiring someone in or training up their top engineers all ensure that someone will be ready to keep the project rolling.
In healthcare, following these steps and implementing successful AI solutions is saving lives and transforming patients' relationships with healthcare companies. We could all learn something from these healthcare initiatives and help change the world for the better because the truth is, AI has the power to do so much good – not just in healthcare but across all industries. All it takes is for someone to believe they can make a customer’s life a little bit easier or a little bit better with AI and to act on it. The power to transform industries, using the stuff we dreamed about as kids, is here – we all just need to seize the inspiration to take the first step.
About The Author
Santosh Rao is NetApp’s head of AI/ML/DL.