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The 3 Questions Every Product Leader Should Ask When Evaluating a New AI Tool

Ranjan Goel
VP of Product
LogicMonitor

All eyes are on the value AI can provide to enterprises. Whether it's simplifying the lives of developers, more accurately forecasting business decisions, or empowering teams to do more with less, AI has already become deeply integrated into businesses. However, it's still early to evaluate its impact using traditional methods. Here's how engineering and IT leaders can make educated decisions despite the ambiguity.

1. Does my current team have the technical ability to implement this?

Even the most advanced technology won't deliver its full potential if it isn't implemented and maintained properly. Leaders must ask:

Can my existing team do this? Can we train them to do an AI implementation in a timely manner?

Or will we need to hire additional staff?

None of the answers to the above questions spell disaster for implementing AI, they do help create a clearer picture of what's possible for your specific team. Given how quickly AI is evolving, upskilling or reskilling is likely required for most organizations. Whether through training or hiring, implementation needs to be feasible.

2. Am I willing to implement this at its current stage?

AI is full of promises — some near-term, some further off. When evaluating AI vendors, it's important to recognize that the technology's current capabilities may continue to evolve rapidly. If the current proof of concept meets most of your needs, great!

Decision makers should evaluate whether the AI tool provider they're entertaining is open to working closely to iterate the tool. Most AI tools are not yet mature enough for all potential use cases to be available already.

3. So you want to move forward. How do you justify the investment?

Think of the ROI of AI as falling into two categories: business benefits and financial benefits.

Most AI tools today offer value in terms of business benefits, such as improved customer experience, enhanced employee productivity, and faster rollouts of new features or products. Businesses using AI can differentiate better from competitors as more innovative in their products and service offerings.

The other category is financial benefits, which, in addition to the above, will undoubtedly catch the attention of the C-suite and board of directors. These include factors like improved top-line growth or improving margins. Quantifying solid financial benefits from AI tools is starting to make its way, especially for domain-specific AI applications like IT operations, medical or retail. This is an area where a partnership with the AI tool vendor and decision-maker can greatly improve the quality of ROI calculation to account for key use cases.

It's rarely one person's responsibility to ask and answer all these questions. These considerations should involve the broader team and be viewed holistically. Some tools that are still in their infancy may be worth the risk if they check many of the other boxes. A more significant monetary investment could be the right choice if the technology addresses a critical need for your team that otherwise couldn't be met. Ask these questions, and reevaluate often.

Ranjan Goel is VP of Product at LogicMonitor

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The 3 Questions Every Product Leader Should Ask When Evaluating a New AI Tool

Ranjan Goel
VP of Product
LogicMonitor

All eyes are on the value AI can provide to enterprises. Whether it's simplifying the lives of developers, more accurately forecasting business decisions, or empowering teams to do more with less, AI has already become deeply integrated into businesses. However, it's still early to evaluate its impact using traditional methods. Here's how engineering and IT leaders can make educated decisions despite the ambiguity.

1. Does my current team have the technical ability to implement this?

Even the most advanced technology won't deliver its full potential if it isn't implemented and maintained properly. Leaders must ask:

Can my existing team do this? Can we train them to do an AI implementation in a timely manner?

Or will we need to hire additional staff?

None of the answers to the above questions spell disaster for implementing AI, they do help create a clearer picture of what's possible for your specific team. Given how quickly AI is evolving, upskilling or reskilling is likely required for most organizations. Whether through training or hiring, implementation needs to be feasible.

2. Am I willing to implement this at its current stage?

AI is full of promises — some near-term, some further off. When evaluating AI vendors, it's important to recognize that the technology's current capabilities may continue to evolve rapidly. If the current proof of concept meets most of your needs, great!

Decision makers should evaluate whether the AI tool provider they're entertaining is open to working closely to iterate the tool. Most AI tools are not yet mature enough for all potential use cases to be available already.

3. So you want to move forward. How do you justify the investment?

Think of the ROI of AI as falling into two categories: business benefits and financial benefits.

Most AI tools today offer value in terms of business benefits, such as improved customer experience, enhanced employee productivity, and faster rollouts of new features or products. Businesses using AI can differentiate better from competitors as more innovative in their products and service offerings.

The other category is financial benefits, which, in addition to the above, will undoubtedly catch the attention of the C-suite and board of directors. These include factors like improved top-line growth or improving margins. Quantifying solid financial benefits from AI tools is starting to make its way, especially for domain-specific AI applications like IT operations, medical or retail. This is an area where a partnership with the AI tool vendor and decision-maker can greatly improve the quality of ROI calculation to account for key use cases.

It's rarely one person's responsibility to ask and answer all these questions. These considerations should involve the broader team and be viewed holistically. Some tools that are still in their infancy may be worth the risk if they check many of the other boxes. A more significant monetary investment could be the right choice if the technology addresses a critical need for your team that otherwise couldn't be met. Ask these questions, and reevaluate often.

Ranjan Goel is VP of Product at LogicMonitor

Hot Topics

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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