Generative artificial intelligence (GenAI) can improve task-based productivity by quickly summarizing long documents, creating email copies, translating code, and more. But organizations can derive even greater value from GenAI beyond short-term, task-based use.
With its ability to rapidly ingest and process large amounts of data, GenAI can provide deeper insights into what’s happening across your business and recommend actions based on those insights. However, using GenAI to improve your business in such fundamental ways requires an equally fundamental change in how your organization manages its data.
Leaders need to approach their GenAI efforts like a marathon, not a sprint. And just like a long-distance runner needs disciplined training and a strict diet to perform optimally on race day, GenAI needs its own healthy input in the form of organizational data. will do. The suitability of that data will determine whether your GenAI project reaches the finish line or struggles and burns out before it can hit its stride.
Power GenAI with healthy data
Consider how GenAI will change the way you work with data today.
• Democratization: Traditionally, only certain team members had access to your organization’s data to generate reports, build dashboards, and more. But with the right security and privacy controls in place, GenAI can empower more employees to make data-driven decisions and solve business problems.
• Speed: GenAI provides significantly faster time-to-insight, enabling faster decision-making and more immediate action.
• Context: GenAI goes beyond just reporting numbers to providing a deeper understanding of the conditions that led to those numbers. You can provide context and recommendations for each metric to create a comprehensive explanation that drives a holistic understanding of your business.
This enhanced access, speed, and depth of insight requires additional attention to data. If the data you feed GenAI tools is incomplete or inaccurate, the insights and recommendations GenAI generates will be flawed, and so will the decisions and actions you take based on those flawed insights. . This can create distrust in the tool and hinder the deployment of future GenAI initiatives.
Don’t let data stifle your potential
When your enthusiasm for technology is as high as your enthusiasm for GenAI, it’s tempting to ignore the signs of nervousness and keep sprinting forward at top speed. Runners who do this risk career-ending injuries. If he runs GenAI in this way, it can be damaging as well.
Ask these important questions to ensure your data is in the best possible condition.
• How do you manage and collect data? Data must be of the highest quality and reliability. It’s best to monitor data as it comes into your organization, rather than when it already exists and your organization is applying it to internal systems and processes. A governance program that assigns ownership and accountability for all incoming data provides the control you need.
Organizations also need to adapt their data collection methods. Traditional extract, transform, and load (ETL) techniques that are well-suited for structured data can be slow when onboarding other data types such as videos, PDFs, and transcripts. Using a metadata-driven pipeline, data lake Alternatively, you can use a lakehouse architecture to significantly streamline unstructured data collection for your GenAI needs.
• How do you store and manage your data? Does your data reside in departmental, functional, or regional silos? Once you ingest your data, make sure it’s all available to your GenAI tools to ensure your GenAI output is as complete, accurate, and up-to-date as possible. is needed.
However, large-scale data integration efforts don’t have to be undertaken all at once. A good way to start is by testing a small project. data platform And the strategy requires Expand across your organization To help you realize the long-term benefits of GenAI.
• Are privacy restrictions in place and is my data safe? A leader should be—and,—We are particularly concerned about using GenAI safely. Gaining leadership buy-in for a project depends on thoroughly addressing the legal and compliance risks posed by increased data access, data velocity, and context.
GenAI Marathon is a team sport
A healthy data program is more than just technology.your data strategy Data literacy must also be included.Teams need training on best practices Use data responsibly Understanding the best ways to extract useful information from data. (rapid engineering It is rapidly becoming one of the most powerful “programming” languages. )
Providing this support empowers employees to use data and experimentation to uncover insights, ask questions, think critically, and challenge conclusions.
GenAI can play an important role in your organization’s future, but only if it’s built on a sound data foundation. Don’t let your GenAI program hit a wall. Always rely on data you can trust.
Need a GenAI coach? Slalom and Google Cloud can help.
