Adobe AI for Business

What is the difference between predictive, generative, and agentic AI?

Predictive AI is a type of artificial intelligence that builds on machine learning technology to analyze data so you can identify trends and predict outcomes.

Generative AI creates content — text, images, code, video, and audio — from prompts. It focuses on content creation, expression, and summarization.

Agentic AI is a goal-driven system that can take action with human oversight to achieve outcomes. It focuses on action, decision-making, and single- to multi-step execution. Agentic AI builds on generative AI to act autonomously toward a specific goal, like launching a campaign or responding to customer feedback. It can combine predictive and generative models to make inferences, create content, and take action along the way.

What is enterprise AI?

How can enterprise AI improve my company’s efficiency or ROI?

Enterprise AI can:

• Automate repetitive tasks such as invoice processing and customer support.
• Provide predictive insights such as demand forecast and churn prediction.
• Optimize supply chains, marketing campaigns, and sales strategies.
• Enable real-time decisions based on large data sets.

Companies report increased productivity, cost savings, and better customer experiences as benefits of adopting enterprise AI solutions.

Is enterprise AI safe and secure for handling sensitive data?

Which industries benefit the most from enterprise AI?

Every industry can benefit from enterprise AI. Some of the top adopters of enterprise AI include:

• Finance, for fraud detection and risk modeling.
• Healthcare, for diagnostics support and patient management.
• Retail and ecommerce, for increasing personalization and simplifying inventory forecasting.
• Manufacturing, for enhancing predictive maintenance and quality control.
• Logistics and supply chain, for route optimization suggestions and demand planning support.

How do I get started with implementing enterprise AI in my business?

Start with a clear business problem to solve. Then you can:

1. Assess. Evaluate organization readiness and select AI technology that is developed responsibly.
2. Pilot. Identify and prepare priority use cases and pilot them against business and ethical AI criteria.
3. Adopt. Train and enable your organization, then deploy with brand or organizational guidelines in mind.
4. Monitor. Measure performance against business and responsible AI benchmarks for ongoing risk management.

Learn more in The AI Inflection Point