Using Generative AI to Drive Innovation and Efficiency, While Keeping the Human Element

As the digital landscape shifts, generative artificial intelligence (GenAI) tools like ChatGPT and Microsoft Copilot are revolutionizing how businesses operate.

Since its emergence, generative AI has demonstrated its transformative potential, with the potential to add trillions of dollars to the global economy while significantly boosting efficiency and productivity.

McKinsey reports that in less than two years, corporate and business functions such as finance, human resources, and customer care are increasing their investment in generative AI technologies. While early adopters were testing pilot projects with basic generative AI tools a year ago, today, a growing number have implemented generative AI use cases throughout their organizations.

At StormGeo, we are fully embracing this shift, integrating generative AI alongside the invaluable human expertise that has always been central to our mission. This unique combination forms the cornerstone of our value proposition across the industries we serve and the solutions we provide. We understand that AI can amplify the power of human decision-making, but it is human insight that truly drives long-term innovation and success. Our commitment to this synergy is reflected in our goal to automate or augment at least 10% of our internal processes influencing customer experience by the end of 2024. By blending AI capabilities with the depth of our human knowledge, we aim to deliver enhanced solutions that not only meet but exceed our clients’ expectations.

StormGeo’s combination of Human Expertise and Generative AI to drive business innovation

As companies are tracking efficiency gains with generative AI, the real value of this technology lies in its potential to transform business operations.

At StormGeo, we understand that while generative AI offers substantial opportunities for efficiency, its true potential lies in how it can transform business operations. Through the strategic combination of human expertise and advanced AI technology, we not only enhance internal workflows but also deliver significant value to our clients by optimizing processes and offering deeper insights.

Weather Intelligence

Synoptic Text Generation

The challenge
Time-intensive tasks: Meteorologists at StormGeo traditionally spent hours crafting synoptic weather texts. These are written descriptions, accompanying a synoptic weather chart, providing a detailed analysis of the weather conditions observed at a particular time across a specified region. 

An example: "A low-pressure system centered over the North Sea is moving eastward…"

The solution
AI-enhanced workflow: Generative AI is used by our meteorologists to automate the creation of synoptic weather texts based on the data from weather charts. For example, meteorologists input synoptic weather charts and specific instructions (such as the desired length, readability, tone, and key focus areas) into the AI system.

The AI then generates a draft of the weather text, pulling from vast datasets and predefined knowledge bases to ensure that the text accurately reflects current weather patterns and phenomena.

This use of AI reduces the time spent on drafting repetitive, formulaic reports and ensures that the basic structure and content are generated swiftly.

It allows meteorologists to focus their attention on more complex, high-value tasks, such as interpreting weather data and making strategic decisions.

Human expertise: Interpretation and oversight (human-in-the-loop): While generative AI handles the bulk of the drafting process, the human element provided by meteorologists is still crucial for contextual analysis and validation. Human experts bring critical thinking, subjective judgment, and experience to refine the AI-generated texts, ensuring that the final output reflects the nuances of local weather patterns, emerging trends, and unique regional factors that the AI might not fully capture.

Meteorologists can also adjust the AI’s output to match specific communication styles, whether for a technical audience (e.g., aviation or shipping) or a general public audience. This ensures that the final weather text aligns with the needs and expectations of the customer, enhancing clarity, readability, and relevance.

The impact
Efficiency boost: This integration significantly reduces the time spent on routine tasks, saving several hours daily across multiple teams. This leaves meteorologists room to dedicate more time to advanced forecasting and client consultations.

The reduced time spent on such activities also ensures that human meteorologists can focus on contextual analysis and validation. Human experts bring critical thinking, subjective judgment, and experience to refine the AI-generated texts, ensuring that the final output reflects the nuances of local weather patterns, emerging trends, and unique regional factors that the AI might not fully capture.

Automated ISMS Development for Regulatory Compliance

The challenge
The complexity of ISMS implementation: Developing and maintaining an Information Security Management System (ISMS) is a labor-intensive and resource-heavy task. An ISMS consists of policies and procedures designed to systematically manage an organization’s sensitive data. It must also comply with various regulatory frameworks, such as GDPR, NIS2, and ISO 27001.

The solution
Streamlined process: By analyzing legal and regulatory texts, the AI extracts key obligations and generates draft policies. It also automates gap analyses and refines the output through iterative validation with StormGeo’s Chief Information Security Officer (CISO).

Human expertise - Strategic decision-making: AI helps streamline the process by automating repetitive tasks like policy generation and gap analysis, but the CISO is ultimately responsible for strategic decision-making. They assess the overall risk landscape, make decisions about the scope and implementation of security measures, and prioritize initiatives that align with business objectives. CISO’s leadership is necessary to make decisions about which areas to focus on first and how to allocate resources, ensuring that the ISMS remains robust and compliant in the face of emerging threats or regulatory changes.

The impact
Time saved: This approach has saved hundreds of hours during ISO 27001 certification preparations and ensures that ongoing compliance standards are met. The required monthly updates and adaptations to regulatory changes now take 20–30 fewer hours, freeing resources for strategic initiatives.

Maritime Industry

The challenge
Ship data validation process: When onboarding new shipping clients, our Client Services Teams need to assess historical ship performance data. This often contains errors or missing information, and the manual quality-checking (QC) process is time-consuming.

The solution
Data quality assurance: Testing has started where ChatGPT is being deployed to perform a stepwise QC process, addressing errors and validating data at multiple levels:

• Validate Operational Validation Data event and data formats.
• Assess data quality and identify discrepancies.
• Verify fuel balance for accuracy.
• Generate a comprehensive summary report.

Human expertise: Contextual understanding and customer experience: By automating the routine aspects of data validation, the Client Service Team is freed up to focus on higher-value tasks. For example, instead of spending hours manually checking data, they can focus on:

• Customer communication: Engaging directly with shipping clients to better understand their requirements, discuss the data in more detail, or provide tailored insights.
• Customization: Fine-tuning the service offering for the client based on the validated data, ensuring that it meets the client’s unique needs.
• Strategic insights: Analyzing the data for trends or patterns that may inform future operational decisions or improvements in the shipping fleet’s performance.

The impact
Improved operations: This automation has reduced the time spent on QC processes by approximately 50%, enabling the Client Service Team to focus on delivering higher-value services to clients.

Navigating Challenges and the Road Ahead

While the benefits of generative AI are undeniable, the journey to full integration presents several challenges. Key hurdles include addressing data privacy concerns, ensuring seamless system integration, and maintaining human oversight throughout the deployment process. Successfully navigating these challenges is essential to using the full potential of generative AI while safeguarding against potential risks.

At StormGeo, we view this as an evolving process, continuously refining our approach to maximize AI’s potential while mitigating risks.

The Future of Generative AI at StormGeo

As generative AI evolves, StormGeo is dedicated to discovering new ways to apply this technology in line with our mission to provide advanced solutions to industries such as the marine and energy sectors.

By adopting these innovations, we aim to boost operational efficiency, foster creativity, and gain a competitive advantage in the markets we serve.

By integrating generative AI into our processes, we are not just adapting to the future of work, we are shaping it. This technology positions us as leaders in operational excellence, ready to meet the challenges of a rapidly changing world with confidence and innovation.