Five strategies to leverage your data with generative AI
Although AI has been around for decades, generative AI represents a remarkable advance, capable not only of analyzing data or editing documents, but also of creating new content, such as text, images and music. However, AI requires adequate data to function effectively, making it the fundamental basis for technological advances.
Here are five ways to incorporate generative AI into your company’s data to maximize every opportunity:
1. Use generative AI to unlock value from all data:
Currently, only 10% of enterprise data is accessible. However, generative AI has simplified this process, allowing companies to leverage pre-trained models such as Google Cloud‘s PaLM and Gemini to extract insights from unstructured data, tailoring it to their specific needs.
In addition, despite large investments in modern data stacks, enterprise databases are still separated into different silos, making the access needed for training LLM models difficult. This motivates companies to unify their data stored in different platforms in the cloud, ensuring its quality for the success of generative AI.
2. Empower LLMs with semantics that promote understanding and learning
The most common application of generative AI is the creation of advanced chatbots. Next year, 20% of companies are expected to incorporate voice interfaces into their systems.
However, the challenge lies in accurately interpreting business terminology and aligning metrics. Altostratus, using Google Cloud technology, is focused on semantic-based solutions and contextual chatbots to improve understanding and access to business data using advanced techniques and Google Cloud tools such as Looker and LookML to transform the way companies access business intelligence.
3. Unleashing human potential with generative AI:
Generative AI will not only transform traditional business functions such as marketing and finance, but will also open new frontiers for areas such as human resources and office administration. It will also have a major impact on the field of software engineering. This technology will revolutionize the way developers interact with complex systems, enabling them to generate code more efficiently and facilitate interoperability with other systems.
These capabilities will allow professionals to free themselves from repetitive and routine tasks, thus fostering creativity, innovation and problem solving in an increasingly competitive and globalized business environment.
4. Empowering large-scale AI with automation:
According to Gartner, by 2026, more than 80% of enterprises are expected to have implemented generative AI in production environments, compared to less than 5% in 2023. However, building chatbots will not be enough; true adoption of AI will require integrating it into core business processes.
At Altostratus, we develop “Intelligent Assistants” capable of reasoning, making decisions and adapting to changes in the environment, combining automation and generative AI to achieve real transformation and scale efficiency.
5. Reimagine the talent on your teams:
While there is a steady stream of new data and analytics professionals, generative AI requires new skills to harness its potential. A variety of specialized roles emerge, such as AI engineers to manage data and models, AI ethicists to address bias and privacy, and AI optimizers to improve performance and efficiency. At Altostratus, we are leading the way by developing technologies that not only support these roles, but can also automate some of their tasks.
Interested in leveraging your data and implementing generative AI-based development?
Request a consultation meeting with our team.
