IBM’s Armand Ruiz Presents Vision for AI Agents in the Workplace to RNL Leadership Council

IBM’s Armand Ruiz Presents Vision for AI Agents in the Workplace to RNL Leadership Council

Feb 3, 2025 | Press Release

IBM’s Armand Ruiz Presents Vision for AI Agents in the Workplace at AI Leadership Council Meeting 

In a recent presentation to the RNL’s AI Leadership Council, Armand Ruiz, Vice President of Product – AI Platform at IBM, shared his vision for the future of work and the role of AI agents in making it more efficient.

According to Ruiz, AI agents will become a key component of the future of work, enabling tasks to be completed autonomously and freeing up humans to focus on higher-level thinking. “The real promise of AI is in agents, which can actually do work and take action,” he said. “We’re moving into a world where we have multi-agent assistance, where multiple agents work together to achieve a common goal.”

Ruiz also highlighted the importance of addressing the challenges of security, governance, and compliance in the use of AI agents in enterprise settings. “We cannot allow these agents to leak sensitive and confidential information, delete files or send data to the wrong recipients,” he emphasized.

In terms of the future of work, Ruiz predicted that most General AI interactions will be in the form of autonomous agents, with 2/3 or 3/4 of the General AI workforce consisting of agents. He cited the example of GitHub, where an agent can automatically fix bugs and issues, freeing up developers to focus on higher-level tasks.

 

We’re moving into a world where AI will develop AI by itself, and AI will develop agents automatically. – Armand Ruiz

 

Ruiz also discussed the potential impact of AI agents on education, citing the example of a tool that can take notes and create an outline from handwritten notes. “We’re moving into a world where AI will develop AI by itself, and AI will develop agents automatically,” he said.

Regarding the recent developments in deep learning, Ruiz said that the market’s reaction to the release of the DeepSeek model was an overreaction. “We’ve been pushing for open innovation and open source at IBM, and it’s not surprising that someone else has come into the market with a similar model,” he said. 

When asked about the potential impact on decisions related to data centers, Ruiz said that the increased demand for chips and energy will lead to a surge in consumption of AI, particularly in inference workloads. “We see a lot of micro inference going on, and it requires more compute than a regular model,” he explained.

The presentation sparked a lively discussion among the attendees, with several questions and comments from the audience. Ruiz emphasized the importance of addressing the challenges of governance, compliance, working with a trusted partner who understands what you are trying to accomplish with AI, and the need for education and training in the use of these tools.

As the presentation came to a close, Stephen Drew, COO of RNL and chair of the AI Leadership Council, reflected on the importance of working with companies that understand the unique needs of higher education and are committed to the responsible use of AI. “As institutions like RNL continue to navigate the complex landscape of AI and its applications, we are focused on working with our partner universities to help them establish AI governance frameworks, educate their teams on responsible AI, and incorporating AI into our services so our clients benefit from the efficiencies AI offers along with the higher education expertise at RNL,” he said.

To learn more about RNL’s AI governance services and how they can support your institution’s AI initiatives here.

 

RNL Featured in Inside Higher Ed

RNL Featured in Inside Higher Ed

Dec 10, 2024 | Press Release

Rebecca Jenkins

Excerpt taken from the Inside Higher Ed blog by Joshua Kim and Edward J. Maloney

The new RNL report, “Online Program Marketing and Recruitment Practices: How Online Programs Are Leveraging AI, Communications Planning, ROI, and More to Maximize Yield,” is a must-read for anyone working in online program marketing and recruiting.

With the significant focus that the report gives to AI usage and planning, we sat down with Rebecca Jenkins, director of product marketing at RNL, to discuss some of the most interesting things that the report surfaced about current usage of and attitudes about AI. Rebecca has a unique perspective as someone with a deep background as an institutional marketing leader.

We asked her four questions.

Q: Was there any finding that stood out among all the others in terms of AI in higher education?

A: One thing that was surprising in the study is how many people are planning to or currently use AI for online marketing and recruiting. This doesn’t just extend to the people who are in the trenches and are trying to figure out how to get all the work done and still engage with students at the same time. This also extends up through senior leadership. The study showed that nearly half of senior leadership or cabinet-level individuals are receptive to implementing AI solutions, and nearly 90 percent of marketing and recruitment leaders are receptive—with a considerable share being “very receptive.”

This strongly indicates that AI enrollment solutions are not just something that some are hoping can be implemented but that they will be implemented. Conversations about AI are happening all over now, and with these data, enrollment and marketing leaders can be confident in saying that there is a lot of receptivity across the nation in marketing and recruitment operations, as well as among institutional leadership.

To read the other three questions, read the full blog here.

RNL Launches New AI Essentials Online Courses

RNL Launches New AI Essentials Online Courses

Dec 6, 2024 | Press Release

Gain the Knowledge and Confidence to Harness AI for Your Professional and Academic Success

December 6, 2024 – RNL, a leading provider of higher education solutions, is excited to announce the launch of its new AI Essentials for Higher Education on-demand course. This comprehensive course is designed to demystify artificial intelligence and equip higher education and nonprofit professionals with the essential knowledge to leverage AI for their organizations.

The 90-minute asynchronous course offers a clear and concise introduction to AI, covering fundamental concepts such as machine learning and generative AI. Participants will gain insights into the practical applications of AI in higher education, including enrollment management, fundraising, and operational efficiency.

Upon completing the course, participants will receive an RNL AI Essentials Certificate of Completion and a digital badge to showcase their achievement on social media and professional networking platforms.

To further delve into the world of AI, RNL offers a suite of advanced courses: AI in Enrollment, AI in Fundraising, AI Cultural Shifts, and AI Governance. These courses explore the transformative impact of AI on higher education and provide actionable strategies for implementing AI-driven solutions.

Course Details:

  • AI Essentials for Higher Education (90-minutes):

    • AI Basics: Understand the fundamentals of AI and its real-world applications.
    • Machine Learning: Learn about different types of machine learning and how computers learn from data.
    • Generative AI: Explore the power of AI to create new content.
    • AI Tools: Discover the best AI tools for higher education and nonprofits.

RNL AI Master Practitioner Courses (Approximately 4 hours total):

  • AI in Enrollment:

    • Leveraging AI for Enrollment and Recruitment
    • AI Tools for Admissions
    • AI and Bias in Enrollment
  • AI in Fundraising:

    • AI in Fundraising
    • Personalized Donor Segmentation
    • Improved Donor Engagement
    • Alumni Outreach
  • AI Cultural Shift:

    • Navigating the AI Cultural Shift
    • Effective Communication in the Age of AI
  • AI Governance:

    • Understanding AI Governance
    • Developing an AI Governance Framework
    • AI Governance Best Practices

Completing all five courses earns participants an RNL AI Master Practitioner Certificate of Completion and a digital badge.

For more information and to enroll, visit Enroll in our free AI Essentials course today!

Congrats to our RNL AI & EDU Contest Winners!

Congrats to our RNL AI & EDU Contest Winners!

Nov 6, 2024 | Press Release

November 6, 2024 – RNL is excited to announce the winners of our AI & EDU contest, recognizing the most innovative ideas for transforming higher education. These winners have demonstrated exceptional creativity and a deep understanding of how AI can revolutionize student enrollment, donor engagement, retention, and campus efficiency.

The winning ideas, submitted by:

  • Melody McMillan from Seattle Colleges
  • Dr. Katie Lentz from Palm Beach Atlantic University
  • Grant Greenwood from McMurry University
  • Carley Houseman from Medical University of South Carolina
  • Ally Metcalf from The University of Tulsa

Their ideas will be integrated into the RNL Edge product roadmap. These groundbreaking solutions, ranging from streamlining tasks with RNL Answers to unlocking new fundraising opportunities with RNL Insights, will soon be available to institutions across the country.

RNL is committed to empowering higher education institutions with cutting-edge technology. By recognizing and implementing these innovative ideas, we are paving the way for a future where AI drives student success and institutional growth.

Dr. Stephen Drew on The Chief AI Officer Show: Unpacking the Explainability Challenge in AI

Dr. Stephen Drew on The Chief AI Officer Show: Unpacking the Explainability Challenge in AI

Nov 1, 2024 | Press Release

 

 

RNL’s Chief AI Officer, Dr. Stephen Drew, tackles the explainability challenge in AI on The Chief AI Officer Podcast.

November 1, 2024

In a recent episode of The Chief AI Officer Podcast, Dr. Stephen Drew, the Chief Operating Officer (COO) of RNL, delved into the intricate relationship between high capability and explainability in neural networks. Neural networks, a type of machine learning model, have revolutionized various industries with their ability to process vast amounts of data and make accurate predictions. However, according to Drew, their power comes with a trade-off: they can be very hard to understand and see how they make their decisions.

Why Transparency Matters

Here are a few reasons:

  • Building trust: When we understand how a model works, we’re more likely to trust its outputs and recommendations.
  • Improving model quality: By peeking under the hood of a model, developers can spot biases, errors, and areas for improvement, leading to better performance over time.
  • Taking ownership: With transparent models, organizations can take responsibility for their AI-powered decisions and be accountable for the consequences.

What’s Being Done to Address the Issue

To tackle this challenge, solution providers like RNL are adopting a collaborative approach. They’re working closely with clients to:

  • Set realistic expectations: Educating clients on what AI can and can’t do, so they know what to expect.
  • Develop more explainable models: Creating models that provide insight into their decision-making processes.
  • Foster a culture of transparency: Prioritizing clear communication and accountability within the organization.

A Bright Future for AI

Industry leaders agree that addressing these uncertainties is crucial for successful AI adoption. By prioritizing transparency, we can unlock the full potential of neural networks while maintaining trust and accountability. As Dr. Drew emphasized, finding a balance between capability and explainability is key to successful AI implementation.

Listen to the full episode here.

 

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