What does it mean to be a smarter enterprise, powered by artificial intelligence (AI) and big data? The possibilities reach far beyond today’s chatbots, self-driving cars, and product recommendation engines. McKinsey research suggests that 70% of companies will be using AI by the year 2030, adding trillions of dollars in value to the global economy. AI will allow these organisations to speed up innovation and improve resource allocation. The pace of change promises to be breathtaking.
But getting to this AI-driven future is not without significant challenges. With concerns ranging from skills gaps to tooling complexity to time-to-market pressures, organisations increasingly need an efficient, integrated way to experiment with AI—and move the projects into production.
Big data and AI models
The magic is in the melding of AI and big data. Data of incredible volume, velocity, and variety is fed into the AI engine, making the AI smarter. Then, less human intervention is needed for the AI to run properly. Finally, the AI can deliver deeper insights—and strategic value—from the ever-increasing pools of data, often in real time.
Read more in the Big Data and AI whitepaper:
- Big data in the modern enterprise
- The perfect match: Big data and AI models
- Barriers to adoption and how to overcome them
- Industry use cases for big data and AI
- How to start the big data and AI journey with open source software