5 reasons to adopt AI platforms in 2024

Change is not just a constant—it's a driving force behind growth and innovation. Digital transformation has spurred a digital-first economy over the past two years. Artificial intelligence (AI) and machine learning (ML) are at the forefront, helping organizations prepare for the future, digitalize and permanently reduce business costs.

Yet, many people are skeptical of AI, or work with individuals who are skeptical of AI. What many may not realize is that we’re using AI frequently already, from features like email spam filters to automated customer service chat and digital assistants. In addition to the AI we already work with, there’s so much more to explore as AI models advance and are integrated into a growing array of applications.

5 benefits of AI

1. Enhancing operational efficiency: AI helps streamline operations and improve efficiency across business functions. Through automation and intelligent algorithms, AI can help optimize processes, minimize manual intervention and reduce errors. This translates to cost savings, increased productivity and the ability to reallocate resources to more strategic initiatives
2. Empowering data-driven decision making: Extracting actionable insights from vast amounts of data is increasingly vital in today's business environment. AI equips organizations with tools to analyze data at scale, uncover new patterns and derive valuable real-time insights. By harnessing the power of AI-driven analytics, organizations can make informed decisions faster, identify changing market trends and capitalize on new opportunities ahead of the competition
3. Personalizing customer experiences: Customer expectations are evolving rapidly, and delivering personalized experiences is critical to fostering loyalty and driving growth. AI helps organizations more effectively analyze customer data, predict preferences and tailor solutions to individual needs. Whether through recommendation engines, chatbots or predictive analytics, AI empowers organizations to create more seamless, personalized experiences that drive customer satisfaction and loyalty
4. Fueling innovation and agility: In today's hyper-competitive landscape, innovation is a differentiator and a necessity for survival. AI provides a fertile ground for innovation by enabling experimentation, rapid prototyping and iterative development. From predictive maintenance to predictive modeling, AI helps organizations innovate across diverse domains, increasing agility and helping them to stay ahead of the curve
5. Mitigating risks and enhancing security: With the proliferation of cyber threats and regulatory compliance requirements, cybersecurity has become a top priority for organizations across industries. AI offers advanced capabilities for threat detection, anomaly detection and fraud prevention, bolstering organizations' security posture and helping mitigate risks. By using AI-driven security solutions, organizations can better safeguard sensitive data, protect against emerging threats and simplify compliance with regulatory mandates

While organizations have used predictive AI for years, the advent of generative AI has sparked a renewed focus on how AI can transform every aspect of a business—from reducing costs and providing better customer experiences to delivering better products and services. At the same time, the technology industry has acknowledged the benefits of open source adoption to help eliminate operational silos and improve transparency and interoperability—we continue to see this community-driven approach playing a key role in this new era of AI.

With Red Hat’s enterprise-ready AI platforms, organizations build, develop and use AI-enabled applications to operate more efficiently, drive deeper customer engagement and deliver better products and services. By bringing together a technology partner ecosystem with our platforms, teams can innovate faster, be more productive and more easily leverage AI to achieve everyday business outcomes.

Learn more about accelerating artificial intelligence and machine learning deployments