5 critical steps for AI success

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Test your knowledge: 5 critical steps for AI success

AI PCs and Hybrid AI are just two of the emerging levers for ensuring enterprise success with AI. Take this quiz to see where you line up.

True

False

True or false: Intel AI PCs target niche use cases for enhancing overall productivity or enabling new creative capabilities.

Select the correct definition of “Hybrid AI” and its associated benefits.

The combination of public/private cloud and on-device processing designed to optimize AI performance.

Using the cloud for compute-intensive tasks along with local and edge devices for real-time inferencing and decision making.

All of the above

A delivery model unencumbered by cost, latency, and bandwidth constraints.

Which of the following objectives are most important for AI success?

Reduce latency to increase agility

Automate routine tasks

Optimize workflows to improve operational efficiency

Enhance real-time decision making

True or false: Conducting a comprehensive AI workload assessment can be handled further downstream, once you’re in trial phase.

True

False

Results

The path to AI success has many twists and turns. Understanding how AI PCs can improve productivity across multiple use cases is step one. From there, savvy CIOs will embrace a Hybrid AI model, ensuring the fastest response times for critical decision making. Aligning AI infrastructure with business needs is also essential – another place where Hybrid AI comes into play. To deploy AI successfully, it’s essential to determine where workloads will be handled – in the cloud or at the edge – and conduct a comprehensive assessment of IT infrastructure and data needs early in the planning stages. And last but not least, executives need to draw from a multi-pronged playbook to drive value from AI. Key steps include designing education and training programs, creating a culture of experimentation, embracing formal change management practices, and implementing clear measurement frameworks.

Learn more about Hybrid AI

ANSWER:

False

Explanation: AI is being used to improve productivity in a wide range of use cases across multiple industries – and the early results are very encouraging.

Next question >

Explanation: Hybrid AI strategically combines public/private cloud with on-device processing. This means compute-intensive tasks (ie., large-scale computations) can be performed in the cloud while edge devices, including Intel AI PCs, handle real-time inferencing. Unlike cloud-only AI systems, a Hybrid AI model ensures the fastest response times for critical decision making. In addition to real-time data analysis, Hybrid AI eliminates bottlenecks, improves overall productivity, and aligns AI infrastructure with business needs.

All of the above

ANSWER:

Next question >

Explanation: Aligning AI infrastructure with business needs is essential for AI success. This is where Hybrid AI comes into play. Agility increases as developers are free to iterate and test AI models. This also speeds up deployment cycles for rapid innovation. Leveraging real-time data on Intel AI PCs allows for quicker decision making and more personalized experiences. And hybrid AI-enabled automation streamlines routine tasks, letting employees focus on higher-value work while being more efficient.

All of the above

ANSWER:

Explanation: To deploy AI successfully, it’s essential to determine where workloads will be handled – in the cloud or at the edge. It’s easy to overestimate the capabilities of the edge or underutilize the cloud, leading to inefficiencies and potential resource overload. Conducting a comprehensive assessment of IT infrastructure and data needs early in the planning stages is key. This should include inventory of hardware and software resource as well as Identifying workloads suited for real-time edge processing (ie., low-latency tasks) and those best handled in the cloud (ie., model training, large-scale analytics). Other essential steps include evaluating resource utilization, analyzing network performance, mapping data flows, and ensuring storage solutions meet the demands of both environments.

False

ANSWER:

Which of these tactics is most important for proving business value for AI? (Select one)

Value measurement

Change management campaign

Championing “experimenting” and AI-driven innovation

Education to drive engagement and literacy

Results >

Explanation: Executives need to draw on a multi-pronged playbook to drive value from AI. Key steps include the following: Education is key to bridging skills gaps and fostering AI readiness among employees. Develop training and AI literacy programs to uplevel internal talent while partnering with outside entities for niche or specialized skills. To design a culture of experimentation, consider creating dedicated labs and pilots and incentives through rewards programs. It’s also important to align with tech partners (internal and external) who champion AI innovation. Embrace formal change management practices to reduce cultural resistance, misalignment, or misinformation. Implement clear measurement frameworks. Continuously monitoring ROI metrics will help ensure AI performance stays aligned with business goals.

All of the above

ANSWER:

Using a Lenovo Intel AI PC with Windows 11 Pro can increase productivity by 15%.1 In manufacturing, AI has spurred a 15% increase in sales revenue due to demand forecasting.2 In healthcare, specialists using AI can plan treatments about 2.5 times faster than without AI.3 In education, 55% of educators believe AI has improved educational outcomes.4

From creative tasks like composing text or generating visuals to productivity-enhancing functions like summarizing documents, analyzing spreadsheets, or organizing files and folders, AI is clearly transforming how work gets done.

[1] Per commissioned study delivered by Forrester Consulting, “The Total Economic Impact 4% reduction in legacy technology support costs of Windows 11 Pro Devices,” December 2022 [2] WifiTalents, “AI in Manufacturing Statistics: Transformational Growth and Cost Savings Ahead,” August 2024 [3] Microsoft, “How AI is helping to shrink waiting times for NHS cancer patients,” June 2023 [4] Forbes Advisor, “Artificial Intelligence in Education: Teachers’ Opinions on AI in the Classroom,” June 2024

All of the above

Learn more about Hybrid AI