Real-world deployments of agentic AI have so far been limited in scope, despite strong interest in using the technology to automate many of the business processes now handled by people.

One reason for the slow deployment of agents is the challenge of multi-agent orchestration: the ability of AI agents to communicate with each other and coordinate their activities across enterprise applications, workflows and even corporate firewalls.

There is growing recognition that developing a framework for multi-agent orchestration is essential for deploying agents on a large scale across the entire organization.

In this episode, we explore the main elements of a multi-agent framework, the problems it is meant to address, who is responsible for developing it and where to find ready-made frameworks and tools.

Featuring: Peter Hesse, Partner, 10Pearls

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

• Why the tendency of agents to work in harmony can make them less resilient when their scale expands.
• How a framework can support AI transparency and traceability.
• Using "policy as code" to enforce AI consistency and trust.

References:

• AI agent frameworks: A guide to evaluating agentic platforms
• Real-world agentic AI examples and use cases
• 10Pearls blog post on building enterprise AI agent frameworks

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

Direct materials sourcing is a critical process in product design, engineering and manufacturing. That was never more apparent in 2017 when Tesla began to ship the Model 3, its first electric vehicle meant to be affordable for middle-income buyers.

The company had set two ambitious and unprecedented goals: building an EV for a base price of $35,000 and completing the development cycle in three years, half the typical turnaround in the automotive industry. The compressed timeline put tremendous pressure on employees to source quality parts economically and on time while keeping up with the tight design and production schedules.

But Tesla was working at a disadvantage. Much of its sourcing and procurement was still done manually, and an IT gap existed between the product lifecycle management system, where engineering and design were managed, and the ERP.

In this episode, we explore the impact inefficient procurement can have on profit margins, how a direct materials sourcing platform can close the technology gap for manufacturers, and the role played by AI.

Featuring: Spencer Penn, Co-founder and CEO, LightSource

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

• Why mastering the bill of materials is so important in sourcing's financial impact.
• How LightSource works, who uses it and where it fits in the product lifecycle.
• Lessons learned from Penn's experiences managing engineering finance at Tesla.

References:

• LightSource on procurement's overreliance on email and spreadsheets
• Tesla misses Q3 goals due to "production bottlenecks"
• Automotive supply chains can benefit from sourcing alliances: Here's why.

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

Agentic AI is the hottest trend in ERP. It promises to infuse enterprise applications with AI that anticipates users' needs, communicates with them in natural language and handles more of the tedium of working in ERP systems.

SAP is one of the leaders of the push for agentic AI. It has aggressively added special-purpose AI agents and development tools for building custom agents and beefed up its data platforms to accommodate AI's needs.

But in practice, building agentic AI that works across SAP and non-SAP systems is challenging, and it often requires outside help from a consulting firm or system integrator.

In this episode, we explore the practical realities of implementing AI applications on SAP systems, including the design process, development tools and integration challenges.

Featuring: Gianluca Simeone, Vice President, CTIO and GenAI Leader, Capgemini

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

• Keys to successful agentic AI projects.
• Integration tools and standards for SAP AI.
• Whether non-programmers can use low-code development tools to play a meaningful role in agentic AI design.
• The status of multi-agent orchestration protocols.

References:

• SAP pitches role-based Joule assistants as ERP work partners
• Agentic AI explained: Key concepts and enterprise use cases
• Simeone explains procure-to-pay project in SAP video

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

Controversies over artificial general intelligence (AGI) mostly come down to two big issues: whether it's possible to make computers that are as smart as humans, and whether doing so is worth the risk of AGI somehow turning against its creators.

But what if AGI is not only feasible, but actually dependent on humans, and could ultimately be the ideal collaborator?

The head of an AI research lab asserts that a human-machine symbiosis will be necessary if AGI is ever to attain the "embodied" intelligence of humans: the creativity, intuition and values that go beyond the computational intelligence of today's machines.

In this episode, we explore how this human-machine symbiosis would work in practice, how it could change enterprise applications, and its implications for human intelligence.

Featuring: Nik Kairinos, Co-founder and Chief AI Architect, Fountech AI

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

• How the human-machine symbiosis could solve AI bias and hallucination problems.
• The risk of humans behaving more like machines.
• Why making jobs more efficient with AI could spur job creation.

References:

• Ultimate guide to artificial intelligence in the enterprise
• What is artificial general intelligence (AGI)?
• Fountech AI newsletter

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

Artificial intelligence is starting to transform buy-now, pay-later options and other types of embedded lending by taking over many of the steps of credit approval. It can speed up the information processing, analysis and decision-making of online lending, improve its accuracy and profitability, and ultimately make credit available to more consumers and businesses.

But AI lending also carries the risk of bias against minority groups, and borrowers and lenders must feel they can trust the AI to make fair, fiscally sound decisions. Many banks already have digital infrastructure for online lending and use it to offer loans on websites and retail payment terminals, but they're reluctant to add AI until the regulatory and risk management issues are resolved.

In this episode, we explore how embedded lending platforms work, who uses them, and the benefits and challenges of automating the lending process with AI.

Featuring: Yaacov Martin, Co-founder and CEO, The Jifiti Group

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

• Jifiti's digital lending platform.
• Why embedded lending might be of interest to non-bank enterprises.
• The future of digital finance.

References:

• Injenico, Jifiti partner to offer payment options
• Digital payments to exceed $33.5 trillion by 2030: report
• Yaacov Martin article on bank readiness for AI lending
• Academic study on the rise of digital finance

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

Fraud is among the most common abuses of information technology. Defined as intentional deception to gain an unfair advantage, fraud is increasingly common in talent management, especially recruiting, and has only gotten worse with the easy availability of AI.

For example, AI enables job applicants to misrepresent their qualifications by falsifying resumes and cover letters and tweaking them to match job descriptions. One study showed that the technology levels the playing field so much that companies are less likely to hire the most qualified candidates and more likely to choose the least qualified ones. It's a growing problem for HR departments and hiring managers.

In this episode, we explore the types of HR-related fraud, the role technology plays and strategies organizations can use to minimize its impact.

Featuring: Brian Sommer, Founder and President, TechVentive

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

• How applicants use AI to cheat on tests.
• What technology vendors are doing to address fraud.
• Why holding focus groups with job seekers can improve the recruiting process and provide insight into how people use AI.

References:

• How HR leaders can spot and stop fake job applicants
• Ultimate guide to recruitment and talent acquisition
• Academic study on how AI distorts recruitment

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

Dynamic pricing is an increasingly popular agentic AI application that showcases AI's advantages over humans in certain tasks. In seconds, AI can analyze customer histories and external data to optimize price quotes without turning off customers.

Such labor-intensive work can take salespeople minutes to complete, and they often have biases that cause them to miss opportunities. AI-driven dynamic pricing tools perform the analysis quickly and dispassionately, which is helping to make salespeople more productive and boosting profits.

In this episode, we explore an electrical distributor's use of an Infor ERP dynamic pricing tool, the work that went into developing and deploying it, the challenges, and lessons learned.

Featuring: David Magee, CTO and CISO, Turtle

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

• Turtle's revenue and margin improvements from using the tool.
• Why optimizing prices is so important for large distributors.
• How the Infor AI goes beyond analytics.
• The role of Infor's data science team.

References:

• Infor offers process mining, automation in CloudSuite ERP
• Infor debuts AI agents to tackle industry specific tasks
• Case study on Infor website

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

While ERP cloud migration promises numerous benefits, including cost savings, leading-edge features, broad accessibility and ease of use, it also carries substantial risks. This is especially true of moving the accounting and financial management modules of on-premises ERP to the cloud.

A poorly executed move can break an organization's financial processes and expose sensitive data, raising significant financial and regulatory risks. But establishing internal controls early in the ERP planning process can be an effective safeguard.

In this episode, we explore the kinds of controls that are most effective, who is responsible for them, the steps in developing controls, and where they fit in enterprise application ecosystems.

Featuring: Laura Bellinger, audit and assurance partner, David Rains, audit and assurance principal, Deloitte accounting, controls and reporting advisory.

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

• How AI helps automate the process.
• Why cloud-driven financial transformations are a good time to improve existing controls.
• The role of consulting firms like Deloitte in setting up internal controls.

References:

• Deloitte article by Bellinger and Rains
• What is risk management? Importance, benefits and guide
• What is digital transformation? Everything you need to know

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