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3 Factors Shaping the AI-Driven Enterprise of the Future

Melissa Burroughs
Alteryx

What will the enterprise of the future look like?

If we asked this question three years ago, I doubt most of us would have pictured today as we know it: a future where generative AI has become deeply integrated into business and even our daily lives.

Yet, according to a study by Alteryx, a whopping 82% of the 2,800 IT and business decision makers we surveyed across the globe said that AI is already impacting what their organizations can achieve. While AI has been around for decades, and many have rightfully predicted its potentially lasting impact, this sudden, widespread adoption caught even the best of us off guard.

So, what can business leaders do to help their enterprise prepare for the unknown?

The study, titled Defining the Enterprise of the Future, uncovers market factors significantly impacting organizations, responsible AI adoption, and how the IT workforce should upskill in the future.

1. Dynamic Market Conditions

If the generative AI curveball wasn't enough, now couple this with business challenges we haven't seen in years — high inflation and rising interest rates — as well as ever-increasing data breaches and international conflicts. Businesses of all sizes must now make even more complex decisions to survive today's volatility. Thankfully, this is where AI can help, with 52% stating they will invest in advanced technologies such as AI to respond to the changing market environment.

Embracing the power of accessible AI technology will help enterprises reinfuse transformations to navigate ever-changing economic and tech disruptions. Quickly adopting new technologies like AI may confer first-mover advantages that help capture added revenue, improve customer satisfaction, enhance employee experience, and increase value gained from existing systems and data.

No doubt, boards and senior leaders across industries feel this allure strongly. But before jumping right in to deploying AI across the business, it's important to consider how to do so responsibly.

2. Responsible AI Adoption

While many agree that AI can no longer be ignored, there are still several concerns with the technology, which respondents listed as: data privacy (50%), transparency (41%), data governance (41%), and accountability (36%). IT's strategic management of risks such as these is critical to ensure business resilience in general, and it becomes especially important when rapidly adopting new technologies.

Not adopting AI responsibly could lead to significant damage to your company's reputation, which is why 80% say that AI security, ethics, and governance are key to the success of their organization as they prepare for the future. Ensure you have principles and frameworks in place that help guide how you deploy the technology and integrate it into your portfolio. Leading enterprises and NGOs worldwide have begun publishing their AI operating principles, which often include such aspects as fairness, safety, explainability, social benefit, and human oversight.

3. Upskilling for the Future

Technology alone isn't enough to succeed in the future, and enterprises are looking to hire talent with the right skills for the rise in AI. But the skills needed today will likely not be the same ones needed in three years. In fact, 45% say that while their IT department currently has a need for AI talent, this figure falls to 40% three years from now.

So, what should practitioners look out for to ensure they have the right skills in place?

For starters, they should experiment with new and multiple disciplines, as 72% of business leaders say it is more important for their employees to be multi-skilled than to specialize in one area. Specializing in one area will not be enough in the future — especially for those with the top five skills that many predict will become obsolete: network engineering (29%), repetitive coding (24%), database administration (23%), systems administration (21%), and application support (20%).

While AI is changing everything, it also renews focus on the human side of business. We must determine how to leverage new technologies such as AI to make the best decisions for our organizations, ensure the right policies are in place to support positive outcomes, and upskill talent to contribute meaningfully in a tech-driven world.

Melissa Burroughs is Director of Product Marketing at Alteryx

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Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

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3 Factors Shaping the AI-Driven Enterprise of the Future

Melissa Burroughs
Alteryx

What will the enterprise of the future look like?

If we asked this question three years ago, I doubt most of us would have pictured today as we know it: a future where generative AI has become deeply integrated into business and even our daily lives.

Yet, according to a study by Alteryx, a whopping 82% of the 2,800 IT and business decision makers we surveyed across the globe said that AI is already impacting what their organizations can achieve. While AI has been around for decades, and many have rightfully predicted its potentially lasting impact, this sudden, widespread adoption caught even the best of us off guard.

So, what can business leaders do to help their enterprise prepare for the unknown?

The study, titled Defining the Enterprise of the Future, uncovers market factors significantly impacting organizations, responsible AI adoption, and how the IT workforce should upskill in the future.

1. Dynamic Market Conditions

If the generative AI curveball wasn't enough, now couple this with business challenges we haven't seen in years — high inflation and rising interest rates — as well as ever-increasing data breaches and international conflicts. Businesses of all sizes must now make even more complex decisions to survive today's volatility. Thankfully, this is where AI can help, with 52% stating they will invest in advanced technologies such as AI to respond to the changing market environment.

Embracing the power of accessible AI technology will help enterprises reinfuse transformations to navigate ever-changing economic and tech disruptions. Quickly adopting new technologies like AI may confer first-mover advantages that help capture added revenue, improve customer satisfaction, enhance employee experience, and increase value gained from existing systems and data.

No doubt, boards and senior leaders across industries feel this allure strongly. But before jumping right in to deploying AI across the business, it's important to consider how to do so responsibly.

2. Responsible AI Adoption

While many agree that AI can no longer be ignored, there are still several concerns with the technology, which respondents listed as: data privacy (50%), transparency (41%), data governance (41%), and accountability (36%). IT's strategic management of risks such as these is critical to ensure business resilience in general, and it becomes especially important when rapidly adopting new technologies.

Not adopting AI responsibly could lead to significant damage to your company's reputation, which is why 80% say that AI security, ethics, and governance are key to the success of their organization as they prepare for the future. Ensure you have principles and frameworks in place that help guide how you deploy the technology and integrate it into your portfolio. Leading enterprises and NGOs worldwide have begun publishing their AI operating principles, which often include such aspects as fairness, safety, explainability, social benefit, and human oversight.

3. Upskilling for the Future

Technology alone isn't enough to succeed in the future, and enterprises are looking to hire talent with the right skills for the rise in AI. But the skills needed today will likely not be the same ones needed in three years. In fact, 45% say that while their IT department currently has a need for AI talent, this figure falls to 40% three years from now.

So, what should practitioners look out for to ensure they have the right skills in place?

For starters, they should experiment with new and multiple disciplines, as 72% of business leaders say it is more important for their employees to be multi-skilled than to specialize in one area. Specializing in one area will not be enough in the future — especially for those with the top five skills that many predict will become obsolete: network engineering (29%), repetitive coding (24%), database administration (23%), systems administration (21%), and application support (20%).

While AI is changing everything, it also renews focus on the human side of business. We must determine how to leverage new technologies such as AI to make the best decisions for our organizations, ensure the right policies are in place to support positive outcomes, and upskill talent to contribute meaningfully in a tech-driven world.

Melissa Burroughs is Director of Product Marketing at Alteryx

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...