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AI is now a crucial strategic tool for carving out — and keeping — your competitive edge.
We call it “artificial” intelligence, but the results are all too real. Generative AI helps teams find what they need faster and streamline operations. Organizations like yours are using techniques like retrieval-augmented generation (RAG) to ground outputs in trusted business data, not generic internet sources.
This leads to:
- Improved resource availability.
- Simplified, usable data.
- Actionable business insights.
Here’s how to harness AI for applications that move your organization forward. Start with these four steps.
1. Discover your primary problem.
- Who needs more bandwidth?
- What are your top operational challenges?
- When do time delays slow progress?
- Where can manual effort be reduced?
- Which customer or user experiences have the most friction?
Team leaders and IT decision-makers should ask these types of questions to determine where the organization will gain the most benefit from AI.
2. Define the use case.
Before building, be clear about what you’re solving, how it will work, and what success looks like.
AI is driving possibilities across industries.
Healthcare
- Predictive diagnostics
- Personalized treatment plans
- Automated imaging analysis
- Regulatory monitoring and automation
Financial services
- Risk modeling and fraud detection
- Streamlined lending/underwriting
- Dynamic asset management
- Hyper-personalized experiences
Retail
- Improved in-store and online experiences
- Personalized loyalty programs
- Shrink reduction and inventory control
- AI-powered customer service
Manufacturing
- Simulations and digital twins
- Supply chain forecasting
- AI visual inspection and safety monitoring
- Dynamic pricing models
3. Deliver on business goals.
Align AI app design to core business outcomes. This is how you gain automation and help your organization achieve a host of business goals.
- Increase speed to value.
- Make data-driven decisions.
- Enhance user experiences.
- Optimize operational efficiency.
- Support new product innovation.
- Prove and track ROI.
4. Do it securely.
Security must be foundational. Integrating and building a trusted AI solution means embedding privacy, governance, and explainability into every layer. Partner with trusted industry leaders to drive integrated security from the start and build auditability into your AI solutions.
Regulatory compliance
Monitor evolving government and industry regulations and keep policies updated to maintain continuous compliance.
User training
Guide users with best practices for data privacy, bias detection, and responsible AI use.
Data protection
Protect sensitive data with secure access controls and encryption.
Infrastructure security
Build on security-first platforms like Microsoft® Azure®.
Architect for AI.
Delivering value from AI starts with a strong foundation. Your AI foundation must be built for model compatibility, clean data, and scalable infrastructure.
AI-enabled apps
Modern applications
- Development frameworks intentionally aligned to app goals
- Scalable, flexible infrastructure
- Platform tuned to use case demands
- Automation and monitoring post-deployment
Modern data platform
- Storage tuned to data type and volumes
- Strong governance and security practices
- Resilient, high availability architecture
- Built-in AI and ML for real-time insights
Find support for every stage.
As the leading Solutions Integrator, Insight helps you move from strategy to outcomes at any stage of your AI journey.
Application modernization
Global doughnut chain increases app usability by 40%.
Data platform modernization
Airline outperforms yearly goals by 245% with a modern data foundation.
AI apps
Convenience store chain eliminates manual security monitoring using computer vision.
This is how you gain a solid foundation for AI.
For AI to serve your organization well, you need architecture that’s secure, automated, agile, cost-effective, and aligned to your strategic goals.
