Enterprise Apps Unpacked

"Physical" AI – artificial intelligence embodied in devices like robots, drones and self-driving cars – could be nearing a tipping point, thanks to recent advancements in large language models and agentic AI. The convergence of physical and agentic AI is giving machines the ability to sense their environment, make decisions and take action. Practical business applications are already emerging. They're a major focus of research and development at SAP as the ERP market leader investigates how smart robots and other physical AI devices can work with enterprise applications to make businesses more intelligent and automated. In this episode, we examine trends in physical and agentic AI, how they're transforming industrial automation, and the risks and challenges of implementation. Featuring: Yaad Oren, Global Head of Research and Innovation at SAP and Managing Director of SAP Labs U.S. In today's episode, we'll also cover: References: Smarter robots: Agentic and physical AI converge in businessPhysical AI explained: Everything you need to knowSAP article about physical AI partnerships To learn more about enterprise applications, check out Search ERP.

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: References: AI agent frameworks: A guide to evaluating agentic platformsReal-world agentic AI examples and use cases10Pearls 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: References: LightSource on procurement's overreliance on email and spreadsheetsTesla 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: References: SAP pitches role-based Joule assistants as ERP work partnersAgentic AI explained: Key concepts and enterprise use casesSimeone 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: References: Ultimate guide to artificial intelligence in the enterpriseWhat 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: References: Injenico, Jifiti partner to offer payment optionsDigital payments to exceed $33.5 trillion by 2030: reportYaacov Martin article on bank readiness for AI lendingAcademic 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: References: How HR leaders can spot and stop fake job applicantsUltimate guide to recruitment and talent acquisitionAcademic 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: References: Infor offers process mining, automation in CloudSuite ERPInfor debuts AI agents to tackle industry specific tasksCase 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: References: Deloitte article by Bellinger and RainsWhat is risk management? Importance, benefits and guideWhat is digital transformation? Everything you need to know To learn more about enterprise applications, check out Search ERP.

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: References: Walmart deploys sensors to boost inventory tracking, AI effortsGuide to supply chain managementJournal article co-written by Kumar on IoT in intralogistics To learn more about enterprise applications, check out Search ERP.

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: 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.

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: References: How manufacturers are reskilling factory workers for AI adoption5 challenges of using AI in manufacturingAn overview of Allie's manufacturing software To learn more about enterprise applications, check out Search ERP. To watch the video version our podcast, subscribe to our YouTube channel, @EyeOnTech.

ERP sustainability software mostly focuses on data collection and reporting requirements of environmental, safety and governance (ESG) policies and typically isn't intended to control the business processes that impact the physical environment. But other digital technology has been used for years to monitor and optimize resource use. Now IoT sensors are increasingly paired with digital twins and AI, and linked with ERP and other enterprise applications, to form a complete digital ecosystem for environmental sustainability. In this episode, we explore digital sustainability technologies, their benefits and challenges, and whether more use of the technology will be a net benefit for addressing climate change. Featuring: Peter Weckesser, Chief Digital Officer, Schneider Electric In today's episode, we'll also cover: References: ESG strategy and management: A guide for businessesTech a double-edged sword in race to sustainabilityNext-gen energy: Reimaging the grid of tomorrow To learn more about enterprise applications, check out Search ERP. To watch the video version our podcast, subscribe to our YouTube channel, @EyeOnTech.

The internet transformed corporate learning from a paper-based, in-person process to one that is largely delivered in digital form, on demand from nearly any device or location. More recently, generative AI has provided learning and development (L&D) teams with a tireless assistant that can crank out educational content in minutes. Now AI-powered search is sparking another transformation as employees increasingly use it to find quick answers while they work, learning gradually in ways that suit their personal styles. In this episode, we examine the evidence for the trend, what L&D professionals should do differently, and how the search technology could affect legacy software, especially learning management systems. Featuring: Josh Bersin, Founder and CEO, The Josh Bersin Company In today's episode, we'll also cover: References: Workplace learning: A complete guide for businessesWhat is GenAI? Generative AI explainedGalileo Learn, Bersin's AI-driven HR training tool To learn more about enterprise applications, check out Search ERP. To watch the video version our podcast, subscribe to our YouTube channel, @EyeOnTech.

Generative and agentic AI are rapidly infiltrating enterprise software. But both are prone to data management issues that can hobble their effectiveness and lead to AI hallucinations and faulty decision-making that carry significant risks for businesses. In this episode, we examine an innovative approach that aims to solve these data problems by basing AI models on standard, industry-specific business processes and compliance guardrails while using agentic AI to automate data orchestration across enterprise applications. Featuring: Geraldine McBride, CEO, MyWave In today's episode, we'll also cover: References: MyWave video case studiesWhat is agentic AI? Complete guideAgentic AI governance strategiesSAP sits Joule at the helm of apps, data "flywheel" To learn more about enterprise applications, check out Search ERP. To watch the video version our podcast, subscribe to our YouTube channel, @EyeOnTech.

Procurement has become a strategic priority with significant impact on the bottom line. It's a data-intensive process that requires communicating with large numbers of suppliers, products and services – the kind of complex, transaction-heavy workflow that is uniquely suited to being automated with generative and agentic AI. In this episode, we examine how AI can make procurement more effective and efficient, where it fits in the procurement technology landscape and how it assists – but doesn't replace – humans in the loop. Featuring: Keith McFarlane, CTO, Globality In today's episode, we'll also cover: References: McFarlane explains why agentic AI may herald a golden age for procurement10 real-world agentic AI examples and use casesGlobality CEO on agentic AI and the future of procurementWhat is GenAI? Generative AI explained To learn more about enterprise applications, check out Search ERP. To watch the video version our podcast, subscribe to our YouTube channel, @EyeOnTech.

AI's growing ability to take over human tasks has many people worried about losing their jobs. Some companies are addressing these concerns by educating employees on how to instead use AI as a helper that frees them for more creative work and adds value. In this episode, we explore ways to encourage AI use without mandating it, the kinds of training that work best and how to develop a curriculum that covers different experience levels and jobs. Featuring: Joe Depa, global chief innovation officer, EY In today's episode, we'll also cover: References: What is GenAI? Generative AI explainedThe AI skills gap and how to address itWorkplace learning: A complete guide for businessesHow to implement generative AI for 400,000 employees To learn more about enterprise applications, check out Search ERP. To watch the video version our podcast, subscribe to our YouTube channel, @EyeOnTech.

Digital twins – virtual representations of real-world things – are a hot topic, and they're becoming more capable with the addition of AI and geospatial awareness. In this episode, we explain how AI-enhanced spatial digital twins work, how they're being used today, what it takes to deploy them, and their potential uses. Featuring: Eric Liu, founder and CEO of TwinMatrix Technologies In today’s episode, we'll also cover: References: What is a digital twin?Advantages and disadvantages of digital twin technology How digital twins can help support sustainabilityDebunking the myth: Digital twins are more than just 3D models To learn more about enterprise applications, check out Search ERP. To watch the video version our podcast, subscribe to our YouTube channel, @EyeOnTech.

What separates successful enterprise technology implementations from costly failures? Here on Enterprise Apps Unpacked, we’ll do a deep dive into strategies that actually deliver results. Every other Monday, veteran IT journalist David Essex interviews corporate leaders, industry experts and vendors—the people who are truly in the know—about important developments in ERP, HR and supply chain systems and the other applications that run the business. For business and IT leaders, these conversations cut through the chatter to help them make smart decisions about how they buy, deploy and use enterprise software. Episode 1 drops on August 11, 2025 at 5am ET. Rate and review the podcast to tell us how you like this new content. Find us on YouTube at Eye on Tech or explore our written work on Search ERP.

SAP has faced numerous challenges in recent years, but three big ones stand out: moving its on-premises products to the cloud; convincing customers to adopt its current ERP platform, S/4HANA Cloud; and meeting the unprecedented demand for artificial intelligence by developing practical AI applications. SAP touted significant progress on all three fronts at its annual Sapphire conference, which was held on consecutive weeks this month, first in Orlando and then in Madrid. It repositioned S/4HANA Cloud ERP as a mix-and-match, AI-infused "business suite" – a throwback to the brand name of its previous ERP flagship. It augmented its primary data platform, Business Data Cloud, with prebuilt, composable applications that combine data products with AI and simulation features. And it embedded the Joule AI co-pilot in more business processes across the application suite, making it more autonomous and omnipresent as a user-friendly interface to ERP. The result, SAP claimed, is an integrated "flywheel" of AI, data and apps that feed off each other to accelerate digital transformation. While reaction was generally positive, it was leavened with the wait-and-see attitude that is typical after the ambitious promises and glitzy presentations of a software conference. SAP still has integration and data management work to do if the components of the business suite – especially cloud platforms like Ariba and Concur that it acquired – are to work seamlessly together. In the podcast, three Informa TechTarget editors offer their analysis of Sapphire developments and observations from the Orlando and Madrid events: Jim O’Donnell, news director at SearchSAP; Brian McKenna, enterprise applications editor at London-based ComputerWeekly; and industry editor David Essex. Other topics discussed include: Host: David Essex, Industry Editor, Informa TechTarget Subscribe via Spotify: https://open.spotify.com/show/2TakQHezOu42MCKSQRigDv Subscribe via Apple Podcasts: https://podcasts.apple.com/us/podcast/erp-confab/id1669762576 Subscribe via YouTube Music: https://www.youtube.com/playlist?list=PL5OdmBrO1LpmcDea2Zb-8mNQt0nLg-3SK