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Teresa4Now
Tera Expert

How To Strategically Incorporate AI and Automation Into Your Company

 

Author: Teresa Purdy

 

Throughout my career, I’ve focused on building and leading effective teams and I firmly believe all leadership starts with empathy and understanding your people.

 

Today, leaders can pair empathy with AI, automation, and machine learning to drive efficiency and minimize employee stress. With applications like ServiceNow’s AIOps, Predictive Intelligence, and Automation Engine, organizations can address employee feedback and streamline workflows to retain top talent and ultimately grow at scale. 

 

Our NewRocket Delivery Guiding Principles

New tech is constantly being introduced in the workplace. At NewRocket we developed four guiding principles to help our Crew navigate this changing landscape. Here’s how we design and implement ServiceNow technologies and processes:

 

  1. Processes must be efficient and well understood. We help companies build simple processes while meeting audit, regulatory, and compliance requirements.
  2. Technology must be clean and (close to) out of the box. With several patches and up to two major releases each year, we work with clients to leverage “out-of-the-box” functionality whenever possible.
  3. Foundational data integrity is essential. Successful integrated Enterprise Service Management programs include processes and services that create and consume common data such as configuration items, location, and people data.
  4. Automation and machine learning are game changers. Automation increases efficiency and reliability and enhances the user experience. Automation opportunities also improve delivery and reduce costs and chances for error.

Four guiding principles for success on the AI WayFour guiding principles for success on the AI Way

 

These tenets are fundamental to how we solve customer challenges (we wouldn’t call them “guiding principles” if they weren’t). Each depends on the others; automation and AI-powered solutions only work when the other three principles are in place.

 

The Building Blocks of Robust Automation, AI, and Machine Learning Strategy

Digital transformation doesn’t happen overnight. The journey requires continuous, steady improvements. When leadership combines a digital strategy and data governance in place with an IT roadmap, it generates empowerment, enterprise visibility, and trust across the organization.

 

NewRocket regularly collaborates with ServiceNow, whose Now Intelligence platform automates repetitive tasks so employees can focus on more important work. That’s the ultimate purpose of any sound automation strategy: giving your team more time to accomplish bigger and better things. 

 

For example, ServiceNow's Virtual Agent can pull from previous issues and tickets to offer solutions to employees and with Now Assist for ITSM PRO, agent chat summarization and solution remediation are more ways to increase IT Teams efficiency leveraging the power of Gen AI.  Visibility to value realization showing time saved, cost savings, and incident deflections from these applications via Performance analytics can illustrate how your teams are tracking toward KPIs and spotlight data trends where teams should focus their efforts.

 

Predictive intelligence is another application companies can use to streamline their workflows. It combines AI, machine learning, and automation to deliver insights that help teams work smarter and faster. This application detects major incidents before they occur, automates workflows, and identifies opportunities for improvement. Predictive intelligence does all of that without adding to a team’s workload. Plus, you don’t need a data science expert to set up a predictive intelligence application.

 

Managing multiple business applications in your application portfolio make resolving security, material weaknesses, and conducting real-time audits time consuming without automation.  AI empowers teams to work smarter, not harder; this concept is critical to business resiliency.

 

Finally, we help our clients leverage machine learning to create and even uncover and correct service mapping gaps. Machine learning can also help classify tasks, instances, and other content at scale, offering suggestions to agents to help them solve issues faster.

 

Where Should CIOs and IT Leaders Prioritize Their Efforts?

IT leaders who maintain a growth and predictive mindset contribute more to their company’s success. By leading from a place of empathy and establishing a culture of excellence, you can achieve this mentality. 

 

At NewRocket, I shape a strong culture by promoting positivity without dismissing Crew Members’ stressors and concerns. Automation is a huge help here. Guided by our four principles, we help our clients on The AI Way Path to Success leveraging AI-Powered Service Operations to reduce complexity and enable their business to engage in more meaningful, strategic work.

 

When evaluating applications and solutions, leaders should look for options that generate immediate resolutions and predict issues before they arise. Rather than spending hours analyzing reports and system logs to document causes, employees can work on initiatives that better serve their business stakeholders and customers.

 

For example, businesses can utilize virtual agents, AI-assisted routing, natural language processing, and more to offer quicker and more effective customer solutions.

 

Your entire leadership team must align on digital priorities as well. Incorporate a data-driven growth mindset into your strategy.

  • How are you planning your automation and AI journey in your company?
  • What processes do you need to transform to increase productivity and efficiency?
  • What can help you reach your targets using specific key metrics?
  • What are the biggest areas of disruption in your field and how would you want AI play a role?
  • What initial reactions and thoughts do you have on AI, and why do you feel that way?
  • How fast does your team need to move on AI, and have you assessed what the risks of action vs. the costs of inaction?
  • How do you want to evaluate the impact of AI and its use?

Once you’ve established your goals and roadmap, ensure everyone is on the same page regarding their outputs and timelines.

 

At NewRocket, we focus on partnering with companies that foster cultures of innovation. Prioritizing innovation is vital to successful automation and transformation across an organization. 

 

Automation, AI, and machine learning can lead to impressive business growth. When we harness them properly, we maximize their value and put our teams in a better position to succeed.

 

Teresa is a purpose-driven service leader with over 20 years of experience transforming organizations, projects, and teams. Follow her on LinkedIn.

8 Comments
Troy Dewant
Giga Contributor

Your insights into leveraging AI and automation to enhance efficiency and minimize employee stress really resonate with me. I've seen firsthand how these technologies can streamline workflows and free up valuable time for teams to focus on more strategic tasks.

Rohitstad
Tera Contributor

At my company, we've been exploring ways to incorporate new technologies like ServiceNow's AIOps and Automation Engine into our processes. It's been a learning curve, but we're committed to embracing the potential of AI to drive growth and innovation.Your NewRocket Delivery Guiding Principles offer valuable guidance for navigating the ever-changing tech landscape. I especially appreciate the emphasis on efficiency, data integrity, and the transformative power of automation and machine learning.Speaking of embracing new tech, have you heard about Social Media AI marketing services? It's an area I've been exploring lately, and I'm intrigued by the possibilities it offers for streamlining marketing efforts and engaging with customers more effectively.

Teresa4Now
Tera Expert

@Troy Dewant Thank you for reading my article.  I'm passionate about customer success and helping clients through their ServiceNow journey the right way.  I have a few more articles published here that I hope can be helpful and I'm working on one related to SPM and APM with a focus on The AI Way.  If my article was helpful, I would greatly appreciate a "Helpful" thumbs up!! 😄

 

https://www.servicenow.com/community/riseup-with-servicenow-blogs/creating-a-culture-of-excellence/b...

 

Teresa4Now
Tera Expert

@Rohitstad I'll check out that new tech.  I'm really liking the GONG Marketing AI Features though!! 

 

I'm so happy our guiding principles are helpful.  This is something I'm passionate about . . . helping customers reduce technical debt and set them up for success long-term.  Your exploration of AIOps and AE sounds exciting and I hope to hear more about your ideas on where you want to start.  If you want to reach out and set some time up with me, I'm happy to talk to you about some recommended approaches you can take.  Predictive AIOps is where my practice crew are experts.  BTW, If my article was helpful, I would greatly appreciate a "Helpful" thumbs up!! 😄 

AnooshkaShukla
Tera Explorer

This was an excellent article centering around AI! 

 

It is especially interesting to know about the design and implementation of AI are within New Rocket! The design and implementation steps are lined out with such great detail! The article gives an interesting insight into how AI can be designed, implemented, and for the benefit of everyone! It's especially fascinating given how AI is growing rapidly, especially within the technology infrastructure! 

 

Wonderful article! 

BraydenWS
Tera Explorer

Great insights, Teresa! I completely agree with the importance of AI and automation in driving efficiency and reducing complexity. The four principles you mentioned, especially around clean technology and data integrity, really stand out. Solutions like ServiceNow’s Predictive Intelligence and Virtual Agent are excellent examples of how automation can help teams focus on more strategic work. Excited to see how AI continues to shape the future of business!

Marcos Gianoni
Giga Expert

Teresa, this is an incredibly timely and well-articulated piece. I particularly appreciate the emphasis on starting with empathy, a truly human element, as the foundation for successful AI and automation adoption. It’s a necessary counter-balance to the raw focus on efficiency.

Your point that 'Foundational data integrity is essential' is the bedrock of the entire strategy. Without clean, integrated data (CMDB, location, people), even the most powerful GenAI and Predictive Intelligence capabilities can falter, leading to a loss of organizational trust and failed adoption. It highlights that the strategic investment isn't just in the shiny new tools, but in the painstaking effort of data governance.

Given that the pace of Generative AI introduction (like Now Assist) is currently outpacing most organizations' ability to solidify their foundational data integrity, how can IT leaders best manage the tension between the immediate need to deploy cutting-edge AI features and the long-term, arduous task of truly perfecting their underlying data architecture?"

Teresa4Now
Tera Expert

@Marcos Gianoni - Thank you for your feedback and question!  You’ve brought up a critical challenge . . . the pace of AI tooling is accelerating, often faster than an organization’s data architecture can keep up. Rather than treating that as an either/or decision, I believe the smartest route is “parallel tracks”: deliver early value where risk is low, while simultaneously investing in data foundation and governance.

 

On one track, pick low-risk, high-value use cases (e.g., internal knowledge-base search, FAQs, non-sensitive automation) that can benefit from AI now.  These help build user trust and demonstrate tangible benefit without exposing critical data. On the other track, formalize your data strategy and governance: establish data owners, standardize and validate core data (CMDB, people, location), define classification and access policies, and build processes for ongoing data hygiene.

 

In parallel, establish governance around AI itself: create a cross-functional body (e.g., an AI Center of Excellence + model governance committee) to set policy, vet use cases, and manage risk. This I would say "early but cautious adoption with disciplined data and AI governance" approach, lets organizations get some value from “shiny new tools” now, while steadily strengthening the foundations that will sustain long-term success.

 

I believe that approach balances the competing pressures, delivering value without sacrificing data integrity or long-term trust.

 

Here is a sample of low-risk/high-value use case you can start with (using Moveworks & ServiceNow):

  • Self-Service IT / Employee Service Requests (Routines & Repetitive Tasks)
    • Use an AI agent to handle simple, repetitive IT service-management tasks: password resets, software access requests, common incident submission, standard ticket routing, and basic troubleshooting. 

    • These are “low stakes” tasks: the impact of a minor error is limited, and human oversight can be retained if needed. This makes it a lower-risk way to pilot automation while building trust.

    • Meanwhile, because such automations use existing identity/CMDB/asset data, this use-case helps expose data quality gaps (e.g. missing attributes, outdated records) in a real-world context. That insight is valuable feedback for the data-governance track.

    • More here:  6 Agentic AI Examples and Use Cases Transforming Businesses

Let me know what you think and what is working for you and your company.

 

Regards,
Teresa