AI has disrupted educational technology more than most disciplines. Generative AI tools like ChatGPT cut production time for instructional materials from days down to minutes. Workers can find relevant content more easily, and subject matter experts use the tools to capture and share their knowledge.

Agentic AI brings still more capabilities as agents take over tasks such as the tedious cut-and-paste work and assist instructors by monitoring student activities and answering questions.

In this episode of Enterprise Apps Unpacked, we explore how AI is transforming learning management systems and what senior business and IT managers should do to manage how employees use AI for learning.

Featuring: Zach Pendleton, Chief Architect, Instructure

In today's episode, we'll also cover:

• How AI helps local workforce development efforts.
• The latest features of Instructure's Canvas LMS.
• Challenges of using AI in corporate learning.

References:

• Workplace learning: A complete guide for businesses
• 4 use cases for an LMS with AI
• Instructure's Canvas LMS page

To learn more about enterprise applications, check out TechTarget CIO.

The openness of ERP systems has become controversial when it comes to AI, which needs access to ERP data to learn, understand context and carry out transactions on behalf of users.

ERP vendors are trying to figure out how to make their customers' data available to generative and agentic AI and what kinds of controls to put on it. Some impose certain restrictions while others claim to have a completely open approach.

In this episode of Enterprise Apps Unpacked, we explore the importance of data access in implementing AI in ERP systems, the different approaches taken by two major vendors and how the issue affects AI's ability to handle workflows that cross different applications.

Featuring: Max Fisher, Director of Product Strategy, Infor Velocity Suite

In today's episode, we'll also cover:

• How Infor's data-access approach compares to SAP's.

• Customers who are using agentic AI on Infor CloudSuite ERP.

• How complete the Model Context Protocol (MCP) standard is for multi-agent orchestration.

References:

• Vendors fortify AI in ERP to assure buyers, deter frontier AI rivals

• How to avoid data paralysis with a practical AI data strategy

• Infor Velocity Suite page

To learn more about enterprise applications, check out TechTarget Enterprise Software.

The IT industry consensus seems to be that deploying reliable, enterprise-scale AI requires first getting the data in order. But dissenting voices say that's not necessarily the case and that it's better to achieve small wins earlier than wait for perfect data and risk losing out on opportunities.

That doesn't mean neglecting data cleansing, integration and unification. Those steps are necessary for agentic AI to work across the entire enterprise. And they can be done in parallel with the initial AI app development.

In this episode of Enterprise Apps Unpacked, we explore how to implement a dual-track AI data strategy, how AI itself can speed up and improve data management, and why defining business value first is essential.

Featuring: Helena Jochberger, VP and Global Lead of Manufacturing and Consulting, CGI; Gaby Martin, Director, National AI Strategy & Technical Lead, CGI U.S.

Today's episode also covers:

• How CGI clients successfully followed the strategy.
• Lessons learned.
• Talent issues, including the role of data scientists and outsourcing.

References:

• Can industry process models fix the agentic AI data problem?
• How agentic AI amplifies data management challenges
• Jochberger blog post on how the C-suite is rethinking AI

To learn more about enterprise applications, check out TechTarget Enterprise Software.

Organizations are starting to recognize they can use AI not just to do existing work faster, but to change what kind of work is done and who does it. They need a plan for redesigning work itself.

Popular methodologies for making business processes and workflows more efficient and productive, such as Six Sigma, lean management and Agile development, hold lessons for companies struggling with how to deploy AI on an enterprise scale.

In this episode of Enterprise Apps Unpacked, we explore how lean and Agile practices can help redesign workflows to take full advantage of the speed and scale of AI.

Featuring: Andrew Sales, Chief Methodologist and Chief Product Officer, Scaled Agile

In today's episode, we'll also cover:

• How AI is transforming software development.
• Scaled Agile's new AI-Native SAFe framework.
• Common mistakes in AI deployment.
• Best practices.

References:

• How to escape agentification pilot purgatory for scalable AI
• Why EY built an entire AI platform for enterprise-scale agentic AI
• Scaled Agile's AI-Native SAFe web page

To learn more about enterprise applications, check out TechTarget Enterprise Software.

Candidate fraud has become a major problem in recruitment as job applicants use AI to blast employers with misleading or false information about their experience, education and skills. It also presents security risks by making organizations vulnerable to people with nefarious motives like intellectual property theft and network sabotage.

Recruiters struggle to stay ahead of the problem. The solution could be to fight fire with fire and use AI itself to combat this AI-driven phenomenon.

In this episode, we explore what candidate fraud is, why it's becoming more widespread, and how recruiters are responding by changing how they conduct job interviews -- all with the tireless assistance of AI.

Featuring: Dimitri Boylan, Founder and CEO, Avature

In today's episode, we'll also cover:

• How AI detects fraudulent candidates.
• Avature's AI-enabled talent management and recruiting platform.
• Using AI to automate mundane tasks and make more time for face-to-face interviews.

References:

• Understanding the science behind AI-based hiring assessments
• Top AI recruiting tools and software of 2026
• Avature article on intelligent automation for hiring managers

To learn more about enterprise applications, check out Search ERP.

For years, visibility was the Holy Grail of supply chain technology. But increasingly, supply chain managers have more visibility than they can handle thanks to the real-time data flooding their dashboards and email systems. What they need now is some way to make sense of the data and act on it.

Decision intelligence could be the answer. It involves using artificial intelligence that can identify the supply chain events and conditions that have the greatest impact, present human operators with relevant information, make recommendations and, in some cases, execute actions on their behalf.

In this episode, we explore what decision intelligence is, the role of agentic AI, and where decision intelligence technology fits in the ERP and logistics software ecosystem.

Featuring: Jett McCandless, Founder and CEO, project44

In today's episode, we'll also cover:

• Features of project44's decision intelligence platform.
• Who uses the platform.
• How the AI knows which data to prioritize.
• Remaining challenges of supply chain visibility.

References:

• What is supply chain visibility and why is it important?
• 11 benefits, use cases for AI in logistics
• Project44 on the future of supply chain decision intelligence

To learn more about enterprise applications, check out Search ERP.

Having completed the herculean task of training 400,000 employees to use generative AI, EY, the Big Four accounting and IT consultancy, found itself with another major challenge: how to respond to the opportunities and challenges of the agentic AI wave.

EY's ambitious solution was to partner with Microsoft and Nvidia to develop a multi-layered AI platform, or "operating system," that unifies the intelligence, orchestration, data, workflows, governance and domain experience of the company's generative and agentic AI technology.

In this episode, we explore what an agentic AI platform strategy involves and how companies of all sizes can benefit from it.

Featuring: Julie Teigland, Global Vice Chair of Alliances & Ecosystems, EY

In today's episode, we'll also cover:

• Problems such as AI fragmentation the new platform was designed to solve.
• The basic architecture of the platform.
• Benefits to EY employees, clients and partners.

References:

• How EY is training employees to use AI in their jobs
• Agentic AI explained: Key concepts and enterprise use cases
• EY article on building an agentic AI operating system

To learn more about enterprise applications, check out Search ERP.

Many organizations struggle to develop an AI plan that marshals numerous pilots and employee applications in a unified strategy. Often, they have more pilots than they can manage and are unsure how to get business value from them.

What if the answer is to narrow the focus and try to identify a single, high-impact AI use case that can not only deliver results but provide lessons to apply to future projects?

In this episode, we explore the characteristics of the ideal use case, how to identify and implement one successfully and the advantages of this practical approach to AI-driven digital transformation.

Featuring: Jim Dwyer, Chief Transformation and Innovation Officer, Sutherland

In today's episode, we'll also cover:

• How Sutherland uses this approach internally and with its consulting clients.
• Where companies tend to go wrong in using AI for digital transformation.
• Keys to success.

References:

• How agentic AI can transform ERP for your business
• Enterprise AI adoption: What drives AI at scale
• Sutherland blog post on AI-driven transformation in banking

To learn more about enterprise applications, check out Search ERP.