Enterprise Apps Unpacked

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.