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Implementing AI – A CIO’s Checklist For Success

  David Fafel     Mar 05, 2019

CIO-AI-checklistA global study commissioned by Dell EMC finds that if your enterprise isn’t actively using or pursuing ways to embrace artificial intelligence (AI) for success and risk mitigation you’re being left behind. And considering how fast today’s tech landscape moves, that gap is getting wider—faster.

Specifically, Dell’s study found 51 percent of firms have already implemented or are expanding their implementation of Artificial Intelligence. An additional 20 percent plan to implement AI in the next 12 months. However, to ensure its success and mitigate the risks that come with it, CIOs must take the lead and ultimately drive the enterprise AI agenda themselves. 

CIOs are optimally positioned for this task as the data, applications, server, accelerator, fabric, and storage infrastructures that they manage are critical for driving business value with AI. They can’t do it alone however—their IT teams will also need to transform and become familiar with the new software applications, infrastructure, and platforms necessary for AI, and modernize existing systems to better support the increasing number of AI initiatives. Simultaneously, CIOs must also track the business outcomes AI is driving to sustain and grow further investments in AI.

So where does a CIO start? After a survey of over 350 global enterprises, Forrester Consulting put together a CIO's checklist to guide your transformation efforts, and we agree with the approach. Dig into the checklist below.

1. Engage with the lines of business on their AI needs

Fifteen to twenty percent of the time, lines of business (LOB) completely bypass IT departments when it comes to their AI initiatives. Start rolling ongoing AI projects into IT processes, assess the capabilities that have been developed, and engage business units on their AI goals, challenges, and unmet needs.

Embrace the LOB's momentum and learn from their progress. Share that information within the organization and challenge yourself to learn the newest applications of AI and how they can impact your enterprise.

Use that knowledge to be the go-between for stakeholders and coordinate the investment, energy, and development of AI. Use that authority to proactively drive AI conversations and become the trusted partner on AI initiatives.

2. Start measuring AI’s impact and its progress

Identify, study, and track the key performance indicators (KPIs) that matter most to your enterprise. Use these metrics to assess and justify AI initiatives.

3. Modernize your infrastructure for existing workloads

According to Dell’s report, 64 percent of enterprises reported that outdated and antiquated software was a significant challenge in driving their AI initiatives. Avoid this by moving away from costly legacy technologies that can’t be upgraded and replacing them with software capable of growing and scaling with your enterprise.

Another half to three-quarters of enterprises reported their AI initiatives were hampered by a lack of automation. With an estimated 73 percent of IT spending going towards day to day operations, investing in automation and self-service now will free up resources for new AI initiatives later.

CIOs also need to ensure that their enterprise data integration, database, and data warehouses are ready and capable of handling and powering your AI initiatives.

4. Deploy platforms for building AI solutions

CIOs need to deploy platforms that can enable multiple lines of business to build AI solutions and leverage components from each other’s solutions. For example:

  • Deploy predictive analytics and machine learning platforms that enable data engineers and scientists to collaborate on models and data pipelines across teams.
  • Deploy text analytics, natural language processing, and speech analytics platforms that can be applied to use cases ranging from customer service, marketing, and sales, and can also support the creation of chatbots for both internal and external use.

5. Invest in infrastructure for AI at scale

Invest in the infrastructure hardware required for successful AI transformation. Machine learning, and especially deep learning, requires a new level of computational horsepower, as well as high-bandwidth, low-latency networking and storage.

Sixty-one percent of firms surveyed reported being challenged by a lack of servers with purpose-built processors like GPUs and FGPAs. Over eighty percent pointed to a need for new servers that can handle high-performance computing, as well as accelerators to cut down model training times from days and weeks to minutes and hours. That demand will only continue to grow, so CIOs should invest now in highly scalable, high-performance computing servers with accelerators to support the AI demands of the business.

6. Take charge of the company’s AI strategy

As you become an invaluable partner on AI initiatives, take responsibility for driving the master AI strategy for the enterprise. Ultimately the successes or failures of the enterprises AI ventures will fall on the CIO’s shoulders, whether or not the project was started by them.

7. Build AI capabilities for the company and IT department simultaneously

Assess AI projects that you can support effectively. Begin with technologies that have well-defined use cases, a proven ROI, and relatively mature commercial solutions. Use the KPIs you identified at the onset to track and broadcast AI efforts across the company to keep senior leadership and other stakeholders appraised. Build capability in IT with data science, data engineering, DevOps, and developer skills necessary to build these solutions.

8. Continuously build the business case for further AI investments

Identify, study, and track the business performance metrics that matter most to your company on an ongoing basis. Proving the positive impact of AI to the business will drive increased investment. With meticulous tracking and reporting, the business case for AI investments will be impossible to ignore.

CIOs should also regularly scan for new business opportunities and find new investments—before the lines of business even know about them. Dell’s study found that mature organizations who invest more in AI get more in return. For instance, approximately half of enterprises with an annual spend of $36M in AI expect an ROI between two and five times their initial investment.

Be ready to invest significant portions of the IT budget into new endeavors; it won’t be cheap, but the CIO must drive these new investments and put the priorities of the business as a whole above those of the IT department.

NEXT STEPS: Learn more about how AI in the data center can transform the way you manage IT operations. Click below to read our Tech Brief today.

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Tags  CIO AI Dell EMC

David Fafel

Written by David Fafel

David Fafel, Chief Architect, leads WEI’s long-term technology vision, and is responsible for spearheading development of complex solutions, architecture, as well as application development. David engages with our clients to drive technology design across datacenter environments, cloud architecture and IT strategy. David holds several technical certifications from HP, Cisco, IBM and other leading technology innovators.

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