Five pillars to build AI success

How to build an AI plan that addresses everything from strategy to infrastructure, data to governance, and a culture that nurtures talent.

It all starts with a vision

Take the leap

Every organization needs to establish a strategy that is right for their business. 85% of global companies feel they have a maximum of 18 months to implement their AI strategy before facing significant negative impacts. This can create pressure. In fact, 98% of companies are feeling the urgency to deploy AI or AI-powered technologies over the last six months.

How to create a successful strategy

Establish an AI committee with clear ownership.
Define goals and quantifiable use cases.
Create responsible AI usage guidelines.
Ensure infrastructure is scalable, sustainable, and secure.
Measure progress and outcomes.

98% of all respondents feel the urgency to deploy AI or AI-powered technologies.

Cisco, AI Readiness Index

Invest in a strong foundation

Lay the groundwork

AI and ML deployments will absolutely lead to an increased demand for GPU resources to support network scale and AI workloads. While 95% of IT leaders agree that AI will undoubtedly increase their workloads, only 21% feel they are ready to support the computational demands required to train, support, and meet current and future AI demands.

How to prepare for an AI-ready infrastructure

Understand your organization’s existing compute power usage.
Project required increase in GPUs to ensure optimized network performance and efficiency.
Ensure security capabilities are in place to secure AI workloads and protect data.
Establish support for increased power consumption and the organizational infrastructure changes required to scale.
Measure outcomes.

13% of organizations feel ready to capture AI's potential.

Cisco, AI Readiness Index

Ensure data is organized and traceable

It's all about the data

AI without data is like a lightbulb without electricity. It just does not work. AI depends on clean, centralized, and secure data to establish well-integrated analytics, data sources, and AI platforms. It's critical that the use cases identified align with reliable and available data.

How to make data AI-ready

Ensure hygiene, quality, and reliability of in-house and external data sources.
Organize data to eliminate silos and streamline access.
Align data assets with desired use cases.
Establish efficient data access protocols and procedures.
Train staff on responsible and secure AI usage.

82% of organizations still have their data in silos across the organization.

Splunk Global Threat Research

Govern with guardrails

Responsible AI starts here

Because AI can automatically generate insights that influence decisions and actions, clear governance for how AI is developed and deployed is critical to eliminate bias. These tips can help establish a fair and responsible approach to governing AI usage.

A global effort is needed to create equitable access to artificial intelligence.

_{World Economic Forum Jan 2024}

How to establish governance

Understand risk and impact of AI bias.
Implement mechanisms to detect bias over how AI-based solutions are built, implemented, and operated.
Ensure comprehensive and consistent checks on AI algorithms and impact to existing and future data processing.
Define data handling standards to govern responsible usage of AI.
Measure governance and life cycle management with observability.

51% of respondents say their organization lacks expertise in AI governance, law, and market ethics.

Cisco, AI Readiness Index

Trust in talent

A brave new world

Fear and misconceptions around AI are real and can be scary for workers who worry AI may replace their job or expose a gap in their skills. Embrace the chance to build an AI-ready workforce that can help employees expand their careers and improve their own growth.

Organizations that invest in talent and help employees build new skills will be better positioned to take advantage of planned AI technologies.

How to create an AI-ready workforce

Understand your company's current AI skills.
Identify knowledge gaps and areas for skill building.
Invest in training and hire new talent to build expertise.
Establish proficiency for data handling and security to ensure responsible AI usage.
Measure AI acceptance rate and percent of talent trained on new tools.

31% of all respondents feel they are very well resourced and have the right level of in-house talent to fully leverage AI.

Cisco, AI Readiness Index

Embracing AI in your company culture

Imagine the possibilities

There has been a noticeable reduction in cultural readiness to embrace AI. While the majority of leaders may be eager to get started and take advantage of operational efficiency and performance benefits, the number dropped from 82% last year. Similarly, not all employees are ready to embrace change. These tips can help you connect with employees and create a positive conversation around the possibilities of AI at your company.

How to curate an AI culture

Understand employee receptiveness to AI.
Address AI concerns and internal goals.
Communicate early and often regarding AI plans, best practices, employee expectations, and goals.
Implement mechanisms to detect bias over how AI-based solutions are built, implemented, and operated.
Share AI wins to encourage understanding and adoption.