Is your organization ready for AI? Here’s what to check first

Imagine a world of healthcare where AI-assisted patient-monitoring systems are transforming patient care for the better and AI algorithms analyze medical scans to diagnose illnesses accurately and in record time.

It’s a world where innovation doesn’t end at the hospital door, either. For example, NTT DATA has partnered with Microsoft to provide cloud-native support for JIBO’s small robotic “companions” that keep patients entertained, remind them to take their medication and do their exercises, and alert doctors or nurses in emergencies. 

These technologies are now a reality, and they don’t benefit patients and doctors only. They can also lead to significant cost savings and more efficient staff deployment, among other broader business benefits.

For instance, digital twins – virtual replicas of real-world systems – can help hospital managers monitor the full hospital environment in real time and assess how changes and improvements will affect it.

AI success is about more than just the tools

Of course, it’s not just healthcare that is rapidly transforming. The integration of AI is helping organizations in every industry to navigate complex IT ecosystems and make sense of vast datasets – once they understand how best to leverage AI to maximize its potential.

When NTT DATA presented at this year’s Gartner Data and Analytics Summit in Sydney, Australia, we wanted to highlight the value of AI in revolutionizing business processes, improving decision-making and finding opportunities for growth.

AI can help your organization achieve these goals, but it must be applied in a safe and tested manner to avoid unintended outcomes.

In our example, a hospital can use AI-assisted tools to make medical diagnoses quickly and more effectively. However, if AI systems are not trained, implemented and monitored properly, they may misdiagnose patients – possibly with life-threatening consequences.

So, while AI can simplify complex challenges in your business and make your operations more efficient, you must apply it safely and responsibly.

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Start with your data

To get your organization AI-ready, your first order of business should be to evaluate your data infrastructure and the quality of your data. Ask yourself if you have sufficient data-governance practices in place and if there are data-privacy and compliance considerations to address – you don’t want to implement anything without first addressing any ethics and compliance issues.

As AI technologies become more sophisticated, the ethical implications of their use become increasingly significant. Poor or outdated data can result in biased or incorrect results.

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Without a robust data foundation, your AI implementations are destined to fail. It is a key part of a strategic and stable approach to adopting AI.

Here’s a five-step data checklist for AI readiness:

1. Evaluate your data infrastructure: Assess your current data management systems to see if they can handle large volumes of data efficiently and securely. This includes the hardware, software and network capabilities you’ll need to support AI algorithms that require significant processing power.
2. Assess the quality of your data: Quality data is the lifeblood of effective AI tools. How accurate, complete and consistent is your data? Check for errors, duplication and inconsistencies. Then, determine whether the data is up to date and relevant to the problems the AI is intended to solve.
3. Consider data integration and accessibility: Your data often resides in silos across different departments. AI tools need integrated systems that provide a holistic view of the data they are using. Data must also be easily accessible to authorized personnel and systems.
4. Address compliance and privacy considerations: Before implementing AI tools, you must consider any legal and compliance issues related to data use. This includes understanding and adhering to regulations such as the European Union’s General Data Protection Regulation (GDPR) or the Health Insurance Portability and Accountability Act (HIPAA) in the US. You also need to implement reliable data-privacy measures and, where required, get consent from individuals and institutions to use their data.
5. Establish clear objectives and key performance indicators: What do you hope to achieve with AI? Set clear objectives and identify how to measure the success of your AI implementations. How are they aligning with your business goals and where are they delivering measurable value?

The first step on the path to AI

NTT DATA’s three-week AI Readiness Assessment evaluates your organization’s preparedness to implement and leverage AI technologies.

Focusing on the key pillars of data governance, cloud computing, data management and security, our assessment rates your organization’s maturity in each. We then identify the gaps to address so you can better understand your business needs and current capabilities before you start to apply AI technologies.

Join us in embracing the transformative power of AI.