AI considerations for your cloud adoption strategy
- 10 minutes
AI is revolutionizing cloud adoption strategies by enhancing efficiency, scalability, and innovation. To optimize operations and drive business growth, integrate AI into your cloud platform to benefit from advanced analytics, machine learning, and automation.
Benefits of AI
Improve efficiency and agility. Automate repetitive tasks to save time and reduce operational costs.
Enhance decision making. Get data-driven insights to support more accurate and timely decisions.
Improve customer experience. Get personalized interactions and improved customer satisfaction and loyalty.
Improve scalability and financial efficiency. Expand your capabilities without proportional increases in cost.
Expand innovation. Unlock new products, services, and business models.
Get more value from data. Extract new value from your existing data.
Accelerate sustainability. Use AI to enhance the ability to predict and optimize complex systems, accelerate the development and deployment of sustainable solutions, and empower your workforce to learn and achieve more.
Recommendations
Evaluate AI for business objectives. Identify where generative and nongenerative AI can enhance efficiency and outcomes for your business goals.
Define an AI technology strategy. Choose the right tools and platforms for your AI use cases. Decide whether to buy or build AI solutions. For more information, see Develop an AI strategy.
Inform your organization and decision makers about AI adoption. Familiarize yourself with the Cloud Adoption Framework for guidance about adopting AI on Azure. Use this framework to integrate AI into your cloud adoption strategy.
Educate leadership on AI for sustainability. Learn how AI can transform your organization's sustainability efforts. For more information, see AI transformations for sustainability.
Apply responsible AI principles
The six key principles for responsible AI at Microsoft include fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. Apply these principles to help ensure that your AI is responsible and trustworthy as you integrate it into mainstream products and services throughout your AI adoption.
Responsible AI principles
Fairness: AI should treat everyone equally and avoid discrimination.
Reliability and safety: AI must operate reliably, consistently, and safely to build trust.
Privacy and security: AI should protect confidential information and resist attacks.
Inclusiveness: AI should engage everyone and address exclusion barriers.
Transparency: AI should be understandable and transparent because it can inform important and sensitive decision-making for individuals.
Accountability: AI systems and developers should be accountable for their actions.
The importance of responsible AI
Educate your leadership, decision makers, and the rest of your organization about the importance of responsible AI.
Incorporate responsible AI to help mitigate the following risks:
Unintended consequences: Plan and oversee your responsible AI implementation to reduce the risk of unforeseen effects that have ethical implications.
Evolving threats: Stay ahead of newly emerging threats as AI technology evolves.
Bias: Mitigate bias to help ensure that AI systems are fair and impartial.
Sensitive technologies: Responsibly use sensitive technologies, such as facial recognition, because of their risk to fundamental freedoms and human rights.
Recommendations
Incorporate responsible AI. Integrate ethical frameworks and regulatory practices into your AI plan.
Understand transparency notes for Azure services. Understand how to use Microsoft responsible AI with Azure AI services to inform your cloud adoption strategy and educate others.
Understand Azure AI Content Safety. Learn how to detect harmful content in applications and services. For more information, see Content Safety documentation.
Use inclusive AI design. Use inclusive AI design guidelines to create accessible AI solutions.