Enterprise Apps Unpacked

Direct materials sourcing technology a hub for manufacturers

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.

Capgemini exec shares lessons from SAP agentic AI projects

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.

AI-human symbiosis could be key for enterprise AGI software

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.

AI-driven embedded lending emerges as digital finance option

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.

How AI amplifies resume fraud and other job seeker cheating

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.

How a distributor used AI-driven dynamic pricing for quick ROI

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.

Deloitte experts: Internal controls key in ERP cloud migration

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.

Living up to the hype: Lessons from IoT supply chain wins

The affordable connected sensors made possible by the internet of things seem tailor-made for supply chain management. IoT sensors are ideal for collecting and transmitting the data that companies need for numerous supply chain processes, from traceability and procurement to inventory optimization and logistics.
But has IoT lived up to its initial growth spurt and hype of a decade ago? Recent indications are that it is beginning to show clear value and positive ROI at companies that have implemented IoT in their supply chains.
In this episode, we examine trends in IoT in general and in supply chains, the challenges of deploying IoT, and why widely available AI is boosting IoT's practicality as a business tool.
Featuring: Subodha Kumar, Distinguished Chair and Professor of Statistics, Operations, Data Science and Information Systems, Temple University
In today's episode, we'll also cover:
Which IoT use cases provide the quickest wins.
Where IoT fits into the broader ecosystem of supply chain software.
The future potential of AI-enabled IoT in supply chains.
References:
Walmart deploys sensors to boost inventory tracking, AI efforts
Guide to supply chain management
Journal article co-written by Kumar on IoT in intralogistics
To learn more about enterprise applications, check out Search ERP.

Google union organizer on AI job impact, working conditions

The evidence that AI can eliminate jobs is piling up. Amazon said recently it would lay off 14,000 corporate workers in an effort to become more nimble. The cuts weren't directly tied to AI, but the CEO previously said the workforce would shrink as Amazon continues to embrace AI. Target and UPS announced similar layoffs.
Meanwhile, software vendors announced reductions that were explicitly caused by AI. For example, Salesforce cut 4,000 customer support positions weeks after its CEO said AI was already doing nearly half the work.
In this episode, we examine AI's impact on jobs from the worker's point of view, with insights from people who maintain AI data centers, test the accuracy of search engines and use AI to automate some of their tasks.
Featuring: Shannon Wait, Senior Organizer, Alphabet Workers Union-CWA
In today's episode, we'll also cover:
Efforts to unionize workers to protect them from AI's negative effects.
Federal and state legislation regarding AI and jobs.
Whether AI will be beneficial to jobs in the long run.
References:
Amazon to cut 14K roles in effort to stay 'nimble'
AFL-CIO report, "Artificial intelligence: Principles to protect workers"
AWU-CWA report: "Ghost workers in the AI machine"
To learn more about enterprise applications, check out Search ERP.

AI could save manufacturing from the baby boomer exodus

There's little doubt that AI is starting to eliminate jobs. Recent headlines confirm it. The trend presents a special risk to the manufacturing sector just as baby boomers retire in droves and more companies seek to build up their workforces and reverse the decades-long preference for cheap overseas labor.
But there are positive aspects to AI's impact on manufacturing jobs. Many workers are learning to use it to do their jobs more effectively and prepare themselves for an AI-centric future. Companies are training AI to do work that might not get done at all amid the labor shortages.
In this episode, we explore how using AI to capture and encode the skills of factory workers who are leaving the workforce could keep manufacturers in business, counteract the baby boomer brain drain and make industrial jobs more attractive to young workers.
Featuring: Alex Sandoval, CEO and Co-founder, Allie Systems
In today's episode, we'll also cover:
How Allie's AI, analytics and data platform helps manufacturers monitor and optimize production processes.
Why the software's AI copilot can also serve as a knowledge-transfer and training tool.
Where AI fits in companies' existing learning management and training systems.
References:
How manufacturers are reskilling factory workers for AI adoption
5 challenges of using AI in manufacturing
An overview of Allie's manufacturing software
To learn more about enterprise applications, check out Search ERP.
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