Unlocking the power of data with artificial intelligence
Data is the lifeblood of business – it drives innovation and enhances competitiveness. However, its importance was brought to the fore by the pandemic as lockdowns and social distancing drove digital transformation like never before.
Andrew Brown, General Manager, Technology Group, IBM United Kingdom & Ireland.
Forward-thinking businesses have started to grasp the importance of their data; they understand the consequences of not fully mobilizing it, but many are sat at the start of their journey.
Even the best organizations are failing to extract the maximum benefits from their data while keeping it safe. This is where artificial intelligence (AI) comes into play – it can benefit enterprises with their data in three fundamental ways.
Releasing value
First, without the right tools it is impossible to unlock data’s hidden value. For that to happen businesses need to deploy AI because of its ability to analyze complex datasets and produce actionable insights. These can significantly enhance business agility and improve the foresight of enterprises of all sizes.
The success of any move to adopt AI will depend on a robust IT infrastructure being in place. Transforming data into useful information is only possible with this solid foundation, which in turn allows advanced AI applications to extract the real value locked inside the data.
During the first wave of the pandemic, IBM worked with The Royal Marsden, a world-leading cancer hospital, to launch an AI virtual assistant to alleviate some of the pressures and uncertainty for staff associated with COVID-19. The system depended on fast access to trusted information from various diverse sources, such as the hospital’s official policy handbook as well as data from NHS England. By tapping into these rich knowledge sources, staff were able to get quicker answers to workplace queries while the HR team had more time to handle complex requests.
Unlocking silos
Another issue is that far too many businesses simply don’t know how much data they own. Split up into silos, it can be impossible to gain a clear view of not only what data is available but also where it resides. Removing this bottleneck can also be achieved through the implementation of AI. This is important because incomplete data will result in incomplete insights.
Businesses should prioritize making all data sources as simple and accessible as possible. Cloud computing technologies, such as hybrid data management, have a vital role to play here. Adoption makes it possible to manage all data types across multiple sources and locations, effectively breaking down these silos and a major barrier to AI adoption.
IBM has partnered with Wimbledon for more than 30 years, helping the world’s leading tennis tournament get the most from its data. Tapping into a wealth of new and archived footage, player data and historical records, fans can now benefit from personalized recommendations and highlights reels. Created through a rules-based recommendation engine integrated across Wimbledon’s digital platforms, this personalized content allows fans to track their favorite players through the tournament as well as receive suggestions on emerging talent to follow.
This is all made possible by the hybrid cloud – the data spans a combination of on-premises systems, private clouds, and public cloud. Breaking down these silos has allowed Wimbledon to innovate at pace to attract new global audiences.
Protecting against data theft
While extracting value from data is undoubtedly beneficial for organizations, it also creates risks. Criminals are increasingly aware of the potential to exploit vulnerabilities to disrupt operations or cause reputational issues through leaking sensitive data. The threat landscape is evolving and rising data breach costs are a growing problem for businesses in the wake of the rapid technology shifts triggered by the pandemic.
Over the last year businesses were forced to quickly adapt their technology approaches, with many companies encouraging or requiring employees to work from home, and 60% of organizations moved further into cloud-based activities during the pandemic.
According to the latest annual ‘Cost of a Data Breach’ report, conducted by Ponemon Institute and analyzed by IBM Security, serious security incidents now cost UK-based organizations an average of $4.67 million (around £3.4 million) per incident, the highest cost in the 17-year history of the report. This is higher than the global average of $4.24 million per incident, highlighting the importance of protecting data for British businesses.
AI has a role to play here, and the study revealed encouraging signs about the impact of intelligent and automated security tools. While data breach costs reached a record high over the past year, the report also showed positive signs about the impact of modern cybersecurity tactics, such as AI and automation – which may pay off by reducing the cost of these incidents further down the line.
The adoption of AI and security analytics were in the top five mitigating factors shown to reduce the cost of a breach. On average, organizations with a “fully deployed” security automation strategy faced data breach costs of less than half of those with no automation technology in place.
The sector in which a business operates also has a direct impact on the overall cost of a security breach. The report identified that the average cost of each compromised record containing sensitive data was highest for UK organizations in Services (£191 per record), Financial (£188) and Pharmaceuticals (£147). This highlights how quickly the costs of a breach can escalate if a large number of records are compromised.
Practical steps to protecting your data
The Cost of a Data Breach report highlights a number of trends and best practices that were consistent with an effective response to security incidents. These can be adopted by organizations of all types and sizes and contribute to form the basis of a data management and governance strategy:
1. Invest in security orchestration, automation and response (SOAR). Security AI and automation significantly reduce the time to identify and respond to a data breach. By deploying SOAR solutions alongside your existing security tools, it’s possible to accelerate incident response and reduce overall costs associated with breaches.
2. Adopt a zero trust security model to help prevent unauthorized access to sensitive data. Organizations with mature zero trust deployments have far lower breach costs than those without. As businesses move to remote working and hybrid cloud environments, a zero trust strategy can help protect data by only making it accessible in the right context.
3. Stress test incident response plans to improve resilience. Forming an Incident Response team, developing a plan and putting it to the test are crucial steps to responding quickly and effectively to attacks.
4. Invest in governance, risk management and compliance. Evaluating risk and tracking compliance can help quantify the cost of a potential breach in real terms. In turn this can expedite the decision-making process and resource allocation.
5. Protect sensitive data in the cloud using policy and encryption. Data classification schema and retention policies should help minimize the volume of the sensitive information that is vulnerable to a breach. Advanced data encryption techniques should be deployed for everything that remains.
Developing an AI strategy
So how should a business bring its AI strategy to life? First, organizations must ensure their infrastructure is equipped to handle all the data, processing and performance requirements needed to effectively run AI. If you use your existing storage arrangement without modernizing it, you greatly increase your risk of failure. A hybrid cloud implementation is likely to be the best solution in most instances as it offers the optimum flexibility.
Enterprises should also directly embed AI into their data management and security systems, which should have clearly defined data policies to ensure appropriate levels of access and resilience. The data management system and the data architecture should be optimized for added agility and ease of operation.
Totting up the benefits
A fully featured AI implementation doesn’t just aggregate data and perform largescale analytics, it also enhances security and governance. Together they enable companies to create valuable business insights that fuel innovation. AI will also help ensure that data if used more efficiently and minimize data duplication. But above all, properly managed data is the lifeblood of enterprise – a resource that needs to be identified and protected. Only then can companies start to climb the AI ladder.
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