Predictive Analysis on Impact of Artificial Intelligence in 2024

Integrating AI into various industries may involve more collaboration between AI systems and human workers. AI may be used to enhance human capabilities rather than replace them. Deep learning has been a driving force behind many AI breakthroughs. Improvement in neural network architectures, algorithms, and training techniques may lead to more powerful and efficient models. 

Impact of AI On Industry Automation in 2024

Ramprakash Ramamoorthy, Director of AI Research, ManageEngine, shared his perspective on how AI will impact on Industry automation in 2024, and said, "AI’s impact on industry automation in 2024 is going to be substantial. The more an industry digitises, the greater return on investment (ROI) it can expect from AI. This means industries that have invested heavily in digital technologies are likely to see significant benefits from AI implementation. 

This digitisation paves the way for smart automation on a massive scale, offering a myriad of opportunities for businesses in process optimisation and revenue maximisation. Furthermore, the upcoming year is likely to witness the evolution of foundation models in AI, which will lower the entry barriers and reduce the costs associated with implementing AI for automation. "

Despite the advancements in broad-spectrum AI applications, specialised and narrow AI models will continue to play an essential role, coexisting with larger models to cater to specific industry needs or tasks.

Cybersecurity Concerns in 2024 

on the aspect of cybersecurity-related threats, Ramamoorthy added, "In the realm of cybersecurity, AI has become a game-changer, especially as cyber threats grow in sophistication. AI’s dynamic and adaptive nature has significantly enhanced security systems, moving away from static thresholds to AI-set thresholds that are more effective due to their basis in historical data and past behaviours. Continuous user and entity behaviour analysis (UEBA) has become a norm, with AI constantly monitoring for anomalous behaviour, thus enabling quicker detection and response to security breaches." 

AI’s role is also crucial in providing advanced protection against threats like ransomware, achieved through continuous process profiling. "This shift underlines a stark reality: organisations that haven’t yet integrated AI into their cybersecurity frameworks are increasingly vulnerable to attacks, highlighting the necessity of AI adoption in modern security strategies," Ramamoorthy concluded.

According to SMEStreet's editorial team analysis here are other key trends on AI's impact on industry in 2024:

1. Advancements in Deep Learning: Deep learning has been a driving force behind many AI breakthroughs. Continued improvements in neural network architectures, algorithms, and training techniques may lead to more powerful and efficient models.

2. AI in Healthcare: Expect further integration of AI in healthcare, including diagnostic tools, personalized medicine, and drug discovery. AI algorithms can analyze medical data, assist in early detection, and contribute to more effective treatment plans.

3. Natural Language Processing (NLP) Enhancements: NLP applications, such as language translation, sentiment analysis, and chatbots, are likely to become more sophisticated. The ability of AI to understand and generate human-like language may see significant improvements.

4. AI in Autonomous Vehicles: Progress in autonomous vehicles is expected, with AI systems becoming more reliable and capable of handling complex real-world scenarios. This includes advancements in perception, decision-making, and control systems.

5. Ethical AI and Bias Mitigation: There may be increased focus on addressing ethical concerns related to AI, including bias in algorithms and the responsible use of AI technologies. Efforts to develop fair and transparent AI systems could gain more attention.

6. Edge AI: As edge computing continues to evolve, AI models may be deployed closer to the data source, reducing latency and improving real-time decision-making. This is especially important for applications like IoT devices and smart sensors.

7. AI Regulation and Governance: Governments and organizations may put more effort into creating regulations and frameworks to govern the responsible development and deployment of AI technologies.

8. AI Collaboration with Human Workers: The integration of AI into various industries may involve more collaborative efforts between AI systems and human workers. AI may be used to enhance human capabilities rather than replace them.

9. Quantum Computing and AI: Developments in quantum computing could impact AI by providing faster and more efficient processing for certain types of computations, potentially leading to breakthroughs in AI capabilities.