This article was written by our friends at Databricks. Databricks is the data and AI company. More than 10,000 organizations worldwide — including Block, Comcast, Condé Nast, Rivian, Shell and over 60% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to take control of their data and put it to work with AI.
Dataiku and Databricks recently surveyed 400 senior AI professionals to see how Generative AI (GenAI) impacts businesses in various industries. These professionals included directors, VPs, and C-suite leaders who make decisions about AI and technology in their companies. The results are clear: GenAI is no longer just a buzzword. It improves customer engagement, streamlines operations, and shapes business strategy.
In addition to the survey, a recent webinar featured Conor Jensen, Global Field CDO at Dataiku, and Oliver Chiu, Head of Product Marketing for GenAI at Databricks. They provided insights into the survey results and discussed how GenAI is being used across various industries. They highlighted how companies are using GenAI to enhance customer engagement, optimize operations, and drive innovation.
Jensen and Chiu also addressed the key challenges businesses face, such as data quality, governance, and scaling AI projects. They stressed the importance of having a clear strategy and the right tools, like those offered by Databricks and Dataiku, to unlock GenAI's full potential and achieve long-term success.
Below, we share ten key insights from the survey and webinar that every executive should know.
1. GenAI Is Transforming Business Operations
GenAI is no longer just an experiment. It’s becoming a core part of how businesses operate. In the survey, 81% of companies said they plan to invest at least $200,000 in GenAI over the next year. That’s a significant investment, showing how seriously companies take this technology.
It isn't just about minor improvements. GenAI transforms how businesses engage with customers, make decisions, and drive innovation. It’s essential for automating tasks, predicting trends, and personalizing customer experiences. With so many companies investing heavily, GenAI has become a “must have” for staying competitive. Businesses that don’t adopt it risk falling behind. If your company hasn’t started using it, the message is clear: The time to invest is now.
2. Dedicated Budgets for GenAI
Thirty-three percent of organizations now have a dedicated budget for GenAI projects. This is surprising because GenAI has only recently become mainstream. New technologies typically take years to reach this level of adoption. Companies usually wait before allocating resources to emerging tech. The fact that so many businesses are investing in GenAI shows how it’s catching fire in the industry.
For leaders, this sends a clear message: GenAI is here to stay. If your company hasn’t yet set aside a budget for AI, now is the time to consider how GenAI fits into your strategic plan. Those who invest early will be better positioned to compete as the technology evolves and reshapes industries.
3. Widespread Adoption Across Industries
GenAI is no longer just for tech companies or IT teams. It’s now widely used in industries like financial services, healthcare, retail, and manufacturing. While IT departments often lead the way, GenAI’s impact goes beyond technical operations.
- In financial services, GenAI is improving fraud detection by analyzing large amounts of data in real time.
- In healthcare, GenAI powers diagnostic tools and personalizes treatments to improve patient care.
- In retail, it transforms customer interactions by offering personalized recommendations and services.
GenAI is adaptable and powerful across many sectors, driving innovation in key business areas. The message for leaders is clear: GenAI’s potential is huge and growing fast. If your company hasn’t started using it, you risk falling behind in an AI-driven world.
4. Return on Investment (ROI) Challenges
Here’s some promising news: 65% of companies using GenAI in production are seeing positive ROI.
However, many companies struggle to track and measure these returns. Without a straightforward way to measure GenAI’s impact, it’s hard to justify additional investments. Even if the benefits are real, convincing the board or C-level exec without solid proof is tough.
To gain continued support for GenAI, companies need a clear plan for tracking results. This includes setting specific goals, measuring progress, and ensuring that GenAI projects align with business objectives. Proving the value of GenAI with data is essential for securing further investment.
5. Barriers to Adoption
Like any new technology, GenAI has its challenges. The main barriers include:
- 44% of companies need more resources.
- 28% of companies face employee knowledge gaps.
- 22% of companies deal with IT or governance issues.
These are real problems, but they can be solved. Investing in your people is critical. Training and development will help your team get comfortable with GenAI. Without the right skills, GenAI’s full potential can’t be reached.
Outdated IT systems are another barrier. If your infrastructure is old, now is the time to upgrade. GenAI needs the right technology to run efficiently. Robust IT systems will support AI projects and increase their effectiveness.
6. Data Quality Remains a Major Challenge
One of the biggest challenges with GenAI is ensuring high-quality data. AI models need clean, organized, and reliable data to work effectively. However, many companies still struggle with messy, unstructured data like PDFs and images. Disorganized data leads to poor AI results, bad insights, and wrong predictions.
Businesses need to focus on data management. Teams must clean, organize, and structure data before using it. GenAI's success depends on the quality of the data it processes, so building reliable datasets is crucial.
7. Shift in Sentiment: From Polarization to Pragmatism
In the early days of AI, companies were either extremely excited or fearful of the technology. Now, those extreme feelings have changed. Businesses are taking a more balanced view of GenAI, recognizing both the risks and opportunities.
The fear of AI "taking over" has faded. Companies are thinking more carefully about GenAI’s real impact. This shift is positive. It lets businesses explore AI's potential while managing risks without getting caught up in hype or fear.
8. AI Pioneers vs. Laggards
There’s a clear gap between AI pioneers and companies falling behind. Early adopters see good results. But, they face challenges, especially with scaling GenAI beyond small tests.
Moving from small projects to full production across a company is challenging, even for experienced businesses. If you’re just starting with GenAI, don’t get discouraged. Focus on building a strong foundation first. This includes clean data, clear goals, and a step-by-step plan for scaling AI across the business.
9. Opportunities for Smaller and Mid-Sized Businesses (SMBs)
Interestingly, SMBs may have an advantage with GenAI, in particular the digital native companies. Large companies often struggle with legacy systems and slow decision-making. In contrast, digital natives can move faster and more efficiently.
They can adopt cloud-based GenAI solutions without the need for large, complex systems, allowing them to try AI more quickly. For SMBs, this is a great chance to get ahead of larger competitors by adopting GenAI early. Their agility gives them an edge.
10. Importance of Governance and Security
Don’t mistake speed for recklessness. Successful GenAI implementation requires a solid foundation. As highlighted in the survey, data quality and governance are crucial. Business leaders should ensure they have the right infrastructure and data governance policies in place before scaling GenAI projects. Good data in means good results out — and that’s non-negotiable.
Conclusion
GenAI is no longer a future idea — it’s here and changing businesses in many industries. But adopting GenAI comes with challenges. There are issues like data quality, ROI measurement, governance, and scaling. Companies need the right tools and support to use GenAI effectively and stay competitive.
This is where Databricks and Dataiku come in. The Databricks Data Intelligence Platform provides the infrastructure needed to scale GenAI. It simplifies data management and improves data quality. Its Data Intelligence Engine boosts performance and reduces complexity. It also includes built-in governance and security to keep your AI solutions safe and compliant.
Dataiku makes GenAI easy for all teams, not just IT. Its platform allows both technical and non-technical staff (from the code-free to the code-first) to work together. This way, AI becomes a company-wide resource. Whether you’re just starting or scaling AI across departments, Dataiku works with Databricks to help you get the most out of GenAI.
Together, Databricks and Dataiku offer a simple solution that helps you unlock the full power of GenAI. Their strengths help you stay competitive, innovate faster, and future-proof your business.
The message is clear for executives aiming to lead in the AI-driven future: Start building your AI strategy now. By using the right tools like Databricks and Dataiku, you can ensure success and stay ahead in a fast-changing world. For additional findings, check out the full survey report here.