What AI in 2024 Means for Us?

Introduction

Last week, I shared a post titled “AI in 2024: A Year in Review,” highlighting the groundbreaking advancements in AI technology and their implications across industries. This week, we are narrowing the focus to explore what these changes mean specifically for people working in the utility sector and the IT organizations that support it.

Artificial Intelligence in 2024 has been nothing short of transformative, marking a turning point in accessibility, innovation, and practical application. Groundbreaking advancements in AI models, pricing, and hardware requirements have paved the way for democratization across industries. This blog post examines key developments in AI this year, focusing on their implications for the electric utility industry and IT organizations.

The original article highlights the remarkable strides in AI technology, including cheaper and more efficient models, expanded functionalities like multimodal AI, and the increasing role of open-source platforms. These shifts have broad implications for industries reliant on data and innovation, such as utilities.

Key Highlights

1. GPT-4-class models running on laptops: High-performing models are now deployable without expensive infrastructure.
2. Multimodal AI becoming mainstream: Integration across text, audio, video, and images expands use cases dramatically.
3. LLM token cost reduction: A steep drop in costs opens doors to wider adoption and experimentation.

What This Means

The developments in AI signify a rapid shift toward greater inclusivity and efficiency in technology. Breakthroughs like extended context lengths and real-time multimodal interactions mean that AI is no longer confined to tech giants with deep pockets. Instead, small to mid-sized companies and industries like utilities can now leverage these tools effectively.

The broader availability of AI also raises the bar for innovation, as organizations can experiment with cutting-edge capabilities without being hindered by high costs. However, it also necessitates thoughtful deployment to avoid pitfalls like low-quality content and ethical concerns. Additionally, the quality of data used for AI applications becomes increasingly important. Poor-quality data can lead to unreliable outputs, hindering the effectiveness of even the most advanced models. Utilities must focus on ensuring their datasets are accurate, complete, and up-to-date.

What This Means for the Electric Utility Industry

AI’s evolution presents both challenges and opportunities for electric utilities. Real-time decision-making powered by enhanced inference models and multimodal AI can revolutionize operations.

• Operational Efficiency: AI-driven insights can streamline grid management and maintenance.
• Customer Experience: Enhanced multimodal AI tools improve customer service through personalized and responsive interactions.
• Sustainability: Energy-efficient AI aligns with the industry’s focus on reducing carbon footprints.
• Data Reliability: Ensuring high-quality data sources is critical to harnessing AI’s full potential and avoiding flawed decisions.

What This Means for SCE’s IT Organization

The IT faces a dual challenge: integrating these advancements while maintaining operational stability. On one hand, we must support the deployment of scalable, efficient AI solutions that produce the largest business value, while addressinbg uneven adoption rates in our organizations.

Data quality will play a pivotal role here. IT must implement and enforce strong data governance practices to maintain the integrity and relevance of the information used by AI systems. Regular audits and validations of datasets will help in reducing the risk of unreliable outputs and ensuring the effectiveness of AI-driven initiatives.

IT organizations will need to:

• Train employees to utilize AI tools effectively.
• Develop standards for evaluating AI outputs and applications.
• Align AI strategies with overarching business goals.
• Implement stringent data quality and governance measures.

What I Should Do to Get Ready for This Change

1. Educate Yourself: Stay updated on AI advancements, particularly those impacting the electric utility industry.
2. Experiment with Tools: Explore the AI tools that have been deployed and test their applicability in your workflows.
3. Enhance Skills: Upskill in areas like prompt engineering and multimodal AI applications.
4. Collaborate Across Teams: Work closely with operations and strategy teams to align AI initiatives.
5. Advocate for AI Governance: Be aware of the current AI policies and regulations while supporting and promoting these policies to ensure ethical and effective AI deployment.
6. Prioritize Data Quality: Ensure datasets used for AI applications are accurate, clean, and well-maintained by ensuring that all data is complete, accurate, and aligned to corporate data models and their data stewards.

Conclusion

The rapid progression of AI in 2024 signals a new era of opportunity and responsibility. For industries like electric utilities, this transformation brings the promise of efficiency, sustainability, and enhanced customer experiences. However, thoughtful implementation and ongoing learning are essential to maximize these benefits. At the same time, maintaining high data quality is critical to ensuring that AI delivers reliable and actionable insights.

Call to Action

How are you preparing your organization for the AI revolution? Share your strategies and insights in the comments below!