This is an exclusive article series conducted by the Editor Team of CIO News with Kavitha Srinivasulu, Global Head – Cyber Risk & Data Privacy: R&C BFSI – Tata Consultancy Services (TCS).
Artificial intelligence is becoming a growing trend in today’s digital space. The ability of software or systems to resonate and ease the day-to-day manual activities is done using the booming artificial intelligence technology. Over the past few years, Gen AI has been used across every sector and industry. Using artificial intelligence has particularly been transformative, optimizing processes, enhancing productivity, and providing real-time insights for better decision-making. The amount of data managed by organizations is huge and requires assistance in addressing issues related to analyzing or managing the abundance of data. However, the use of AI reduces these obstacles and helps the organizations manage the data more effectively with zero errors.
Artificial intelligence is a vital affiliate in this age of digital transformation, with specific use cases available across all sectors for securing data. This growing AI technology revolutionizes changing conventional paradigms in a variety of industries, including BFSI, healthcare, manufacturing, retail, and education systems. Grand View Research projects that the worldwide artificial intelligence market will grow at a 38.1% CAGR to reach $1,811.8 billion by 2030, from $136.6 billion in 2022.
AI Vision:
Today, the truth is that the utilization of generative AI across sectors is undeniably profound. This digital transformation leads to various benefits and challenges in securing data, leaving organizations vulnerable to address their security allegations. The weakness in security systems heightens risks to data reliability and decision-making.
Challenges in adopting to GenAI:
As Gen AI is rapidly growing, it’s very important for the organizations to strengthen their security posture while adapting to this evolving landscape. Some of the evident challenges faced across the organizations are:
GEN AI Cybersecurity Top Use Cases:
Artificial intelligence has always been welcomed by industries across the globe for automating jobs, predictive analytics, documentation, customer personalization, evaluating data, and improving decision-making. Gen AI improves operational efficiency by automating repetitive operations, streamlining supply chains, reducing manual efforts, predicting future requirements, and foreseeing unforeseen risks in the huge threat environment. Organizations are working on identifying current business use cases and adapting gradually to fully leverage their potential.
There are different shapes and sizes for implementing Gen AI use cases to increase the cybersecurity controls effectiveness in today’s threat landscape. Let’s look at some of the Gen AI use cases by sector.
Banking and Financial Services (BFSI):
Implementing Gen AI in the banking and financial services sector includes:
- Data Creation and Documentation
- Behavioral analytics and anomaly detection
- Fraud Detection and Prevention
- Credit Scoring and Risk Assessment
- Anti-Money Laundering (AML) Compliance
- Automated Messages during Incidents or for any important communications
Healthcare
The use cases of AI in the healthcare sector include:
- Managing healthcare data.
- Accelerate process optimization.
- Pattern Recognitions
- Proactive incident response
- Personalized Treatment and Therapy
- Electronic Health Records (EHRs)
Retail and E-Commerce
AI use cases in the retail and e-commerce sectors comprise of:
- Boost employee productivity.
- Supply Chain Optimization.
- Fraud Detection and Prevention
- Personalized Shopping Experience.
- Dynamic Price Optimization
- Chatbots for Customer Service.
Manufacturing
The AI use cases in the manufacturing sector encompass:
- Demand Forecasting
- Anomaly Detection
- Supply Chain Optimization
- Customizing services and personalization
- Defect Detection
- Assembly Line Integration
- Predictive Analytics
Automotive
The use cases of AI in the automotive sector are:
- AI-Powered Infotainment Systems
- Auto monitoring systems
- Data Creation
- Intelligent Traffic Management.
- Enhanced Navigation.
- Personalized Customer Experience.
Education
The use cases of AI in the education sector are:
- Personalized Learning
- Documentation and anomaly detection
- Automated Administrative Operations
- Intelligent Tutoring
- Smart Content Creation
- AI in Classrooms for Adaptable Access
- Learning Analytics
Best Practices to embrace and practice before implementing or using Gen AI:
- Target and narrow down the required use cases in the current security posture.
- Initiate a program to understand the risk of internal/external exposures related to gen AI.
- Establish data privacy guidelines.
- Build based on your own data and run using enterprise-grade security to ensure access to data is restricted.
- Establish key metrics to measure expected productivity improvements.
- Adapt documentation and traceability processes.
- Identify and prioritize use cases.
- Create a Center of Excellence
- Experiment with purpose
- Ensure the right set of tools are configured and enabled to protect the infrastructure.
- Prepare and train your team.
In 2024, Gen AI is becoming omnipresent at various places across various sectors, changing the old legacy models and helping organizations make better decisions. Gen AI serves as a crucial tool in bolstering cybersecurity defenses in 2024 and in safeguarding the threat environment and increasing cyber resilience. However, organizations should closely monitor compliance regulations affecting their industry for any changes related to the use of Gen AI systems. The rise of GenAI from 2023 onwards has changed the way security patterns have changed and how much a growing technology can change in a year. As the Gen AI is growing day by day and where it’s headed down the line cannot be predicted, however, a steadfast commitment to facilitating safe and secure systems is paramount to navigating it safely. Organizations should stay committed to its alignment with legal and regulatory requirements without fail throughout the development lifecycle to ensure Gen AI remains a force for uplifting the current security posture to make our environment business resilient and make it more proactive in nature.
About Kavitha Srinivasulu
Kavitha Srinivasulu is an experienced cybersecurity and data privacy leader with over 20 years of experience focused on risk advisory, data protection, and business resilience. She has demonstrated expertise in identifying and mitigating risks across ISO, NIST, SOC, CRS, GRC, RegTech, and emerging technologies, with diverse experience across corporate and strategic partners. She possesses a solid balance of domain knowledge and smart business acumen, ensuring business requirements and organizational goals are met.
Disclaimer: The views and opinions expressed by Kavitha in this article are solely her own and do not represent the views of her company or her customers.
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