Whether you’re starting from scratch or with existing infrastructure, building Artificial Intelligence (AI) requires a different kind of framework than traditional IT. View this infographic for key insights into top concerns, common challenges and expert strategies for building AI infrastructure.
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From networking to compute to storage, Artificial Intelligence (AI) requires a different kind of infrastructure than traditional IT.
While 85% of companies are already using AI to drive business insights, 57% have only just started their journey or are looking to mature their practices.
Accelerate time to value with expert strategies for building AI infrastructure, whether you’re starting from scratch or with existing infrastructure.
Embedded AI services that are part of Platform as a Service (PaaS) or Software as a Service (SaaS) that you already have allow for easier add-ons because the infrastructure is already provided and supported by the service provider. Extending the capabilities that are provided via these services — or creating new ones that integrate with these services — is an easy way to take advantage of AI capabilities without a lot of business resource commitment.
Missed expectations are one of the biggest reasons that AI adoption can fail. That is why it is imperative to develop a clear, data-driven understanding of what AI and Machine Learning (ML) can do to meet the needs of your organization — and how. With this understanding, you can leverage the transformative nature of AI solutions to develop an organizational culture that embraces innovation and adoption of impactful technology.
You don’t necessarily need to hire a team of data scientists to build your AI infrastructure. If you have your organization’s data and approach in order, then automated machine learning (AutoML) techniques can automate the tasks of applying ML to your business problems.
First, understand exactly what your business goals are and what/how AI can help your organization achieve those goals. Then, perform an inventory of your existing data assets and data infrastructure. From here you can determine any gaps between what you have and what you need, prioritize the gaps and apply the 7 R’s to your inventory with attention to your business goals.
Although AI infrastructure can be incredibly beneficial, various roadblocks can make the building process challenging and even discourage organizations from completing their journey. At Insight, we have trained experts that collaborate with clients to solve these challenges and more:
DID YOU KNOW? 86% of organizations have been impacted by technical debt over the past 12 months.
Our experience spans the entire scope of industry technology challenges, empowering you to build your AI infrastructure more quickly, with less risk and with comprehensive support. Choose a strategic partner that understands AI infrastructure.
MarketPulse Research by Foundry Research Services. (February 2023). The Path to Digital Transformation: Where Leaders Stand in 2023. Slide 11. Commissioned by Insight.
MarketPulse Research by Foundry Research Services. (February 2023). The Path to Digital Transformation: Where Leaders Stand in 2023. Slide 16. Commissioned by Insight.