Will AI adoption in ERP be a positive or negative, overall?

Summary

The discussion in this transcript explores the evolving role of AI and technology in society, from McDonald's cashiers relying on computers for calculations to the potential of AI-driven advancements in industries like healthcare and manufacturing. Participants debate the balance between positive and negative applications of AI, stressing the need for ethical guidance. The conversation touches on AI agents' future role in automating tasks, digital twins, and predictive maintenance, emphasizing that while technology evolves, human decision-making and leadership will continue to shape its impact.

Takeaways

• 🤔 Technology is changing traditional skills, with computers now guiding tasks like providing change at McDonald's.
• 👴 Older generations were not allowed to use calculators in school, developing mental math skills instead.
• 📺 Reference to the movie Terminator and concerns about AI taking over by 2028.
• 🛠 Technology can be used for both good and bad purposes, and it's up to leaders to guide it for positive outcomes.
• 🏥 AI has many applications in industries like healthcare, helping improve processes and outcomes.
• 🧑‍💼 It's important for humans to drive the development of AI, making ethical choices on its use.
• 🔓 Concerns about AI being used maliciously, such as through ransomware attacks on organizations.
• 🤖 Distinction between general AI (machine learning) and generative AI (creating text, images, etc.).
• 🏭 Digital twins and AI can help industries, like manufacturing, optimize processes and predict failures.
• 📊 AI agents can autonomously carry out actions, such as raising orders or analyzing data, enhancing business operations.

Q & A

What is the speaker's observation about the skill set changes over time?

The speaker observes that skill sets have changed over time, particularly referencing how employees, such as McDonald's cashiers, now rely on computers to calculate and provide the correct change. This contrasts with earlier times when people had to perform mental calculations without the aid of technology.

How does the speaker relate the evolution of technology to AI and the future?

The speaker humorously refers to movies like *The Terminator* and predicts a future where AI might take control, potentially with robots and drones replacing human roles. However, they express uncertainty about how this will unfold.

What is Judith's stance on AI's potential impact?

Judith believes that, like any technology, AI has both positive and negative potential. She emphasizes the need for ethical leadership and guiding AI's use for good, particularly in industries like healthcare.

What are Nandan's views on the human role in driving AI development?

Nandan argues that AI development is still driven by humans, particularly those at companies like OpenAI, Google, and Amazon. He acknowledges that some people might misuse AI, but he remains optimistic, believing that positive applications of AI will outweigh the negative ones.

How does the discussion address the potential risks associated with AI?

The conversation touches on the risks, such as cybersecurity threats and the misuse of AI by 'script kiddies' who replicate harmful actions. There is concern that fear of AI could cause people to withdraw from using beneficial technologies.

What distinction does Ronald make between general AI and generative AI?

Ronald distinguishes between general AI, which focuses on processing large amounts of data and learning from it, and generative AI, which creates text, images, voices, and other synthetic outputs. He suggests that the dangers of AI lie more in how data can be manipulated.

How does Ronald view the potential for AI in ERP systems?

Ronald sees AI as having a lot of potential in ERP systems, particularly for predictive maintenance, supply chain optimization, and fraud detection. However, he also highlights the challenges of keeping legacy systems running while trying to implement new AI-based solutions.

What are AI agents, and how could they impact industries like manufacturing?

AI agents are tools that act on behalf of users, carrying out tasks such as analyzing data, making predictions, and even executing actions like raising orders. Nandan sees these agents as having significant potential in industries like manufacturing, where they can automate processes and improve efficiency.

What role does synthetic data and digital twins play in advancing AI technology?

Synthetic data and digital twins can help companies create virtual versions of their operations, allowing them to optimize processes and test new strategies without affecting real-world systems. Ronald highlights this as a promising area of AI development, particularly for industries where safety is a concern.

How do the speakers envision AI impacting the future of work and jobs?

The speakers suggest that while AI will automate certain tasks, it will not eliminate jobs. Instead, it will free up workers to focus on more complex tasks and drive business growth. AI will provide tools that help workers make better decisions and complete tasks more efficiently.

Outlines

00:00

🍟 The Shift from Mental Math to AI in Everyday Tasks

This section starts by highlighting the change in skill sets over time, particularly how tasks like giving correct change at a McDonald's drive-thru are now assisted by computers, eliminating the need for the mental math once required. The speaker reflects on the increasing reliance on technology, comparing it to the fears portrayed in movies like *The Terminator* (1984), where robots take over human roles. The discussion hints at the potential future where AI guides more of our actions, similar to how computers are already influencing everyday tasks.

05:01

🤖 Balancing Technology’s Potential for Good and Bad

The conversation shifts to a broader view of technology's impact, with one speaker emphasizing that it is up to humans to guide AI toward beneficial uses. They mention how AI can greatly assist industries such as healthcare but warn of the potential for misuse. The importance of ethics, moral leadership, and strategic investment is highlighted to ensure AI and technological advancements are directed toward positive outcomes. The discussion underscores the delicate balance of harnessing technology for good while being mindful of its risks.

10:02

💻 Are Humans or Corporations Driving AI?

The focus here is on whether large corporations like OpenAI, Google, and Amazon are the real drivers of AI, or if it’s still in the hands of humans. While corporations lead the technological charge, the speaker argues that humans remain the ones determining how AI will be used. There is a recognition that, while some may use AI for negative purposes, historical trends show that the positive applications of technology tend to outweigh the negatives. The discussion also touches on the risks and fears associated with AI misuse, particularly in the realm of cybercrime.

🛠️ The Growing Role of AI in Enterprise Resource Planning (ERP)

This section dives into the distinction between general AI and generative AI, particularly in the ERP (Enterprise Resource Planning) space. AI is more focused on processing data, while generative AI creates text, images, and other outputs. The speaker discusses the challenges and opportunities in using AI for ERP, such as predictive maintenance and fraud detection, and how it can modernize processes. The conversation emphasizes the positive aspects of AI, though there are concerns about errors and manipulation in data processing.

🏭 Digital Twins and AI-Driven Optimization in Industry

The conversation moves to the concept of 'digital twins'—virtual replicas of physical systems that can be used to optimize industrial processes. The speaker notes that while they haven’t seen widespread use in ERP yet, digital twins hold great potential for improving manufacturing processes and embedding AI in industries that require more automation, such as dangerous or health-related fields. The discussion highlights long-term projects involving AI and robotics to optimize factory operations.

🔄 The Future of AI Agents in Business Operations

The discussion here focuses on AI agents, which are seen as the future of AI in business. These agents can autonomously carry out tasks like predicting equipment failures and even drafting purchase orders. The speaker explains how AI agents can improve efficiency by not only providing information but also taking action on behalf of humans. This shift could lead to significant changes in industries like manufacturing, where AI agents could monitor and manage equipment, streamlining operations and reducing downtime.

👨‍💼 Enhancing Efficiency with AI-Powered Systems

This final section wraps up the conversation by tying the role of AI agents back to broader business needs, particularly in integrating data across systems and improving usability. AI can simplify tasks, allowing employees to focus on higher-level work, while AI handles more routine functions like counting change. The speaker emphasizes that jobs won’t disappear but will evolve, as AI enables businesses to handle more complex tasks and grow more efficiently.

Keywords

💡AI (Artificial Intelligence)

AI refers to the development of computer systems that can perform tasks normally requiring human intelligence, such as decision-making, speech recognition, and learning. In the video, AI is discussed in terms of its future potential and impact on various industries, from manufacturing to healthcare. It is seen as a force that could either be harnessed for good or misused for harmful purposes.

💡Gen AI (Generative AI)

Generative AI is a subset of artificial intelligence that focuses on creating new content, such as text, images, and videos, based on input data. In the video, it is distinguished from traditional AI by its ability to generate new information rather than simply process existing data. The conversation highlights concerns about how Gen AI might be used both positively and negatively, particularly in areas like synthetic data creation and content manipulation.

💡Digital Twins

A digital twin is a virtual model designed to accurately reflect a physical object or system. In the video, digital twins are mentioned in the context of manufacturing and other industries, where companies use them to simulate factory processes and optimize their systems. The technology is seen as having significant potential for improving efficiency and safety in industrial settings.

💡Ethics in AI

Ethics in AI refers to the moral principles that guide the development and use of artificial intelligence technologies. The video emphasizes the importance of ethical considerations in AI, particularly when discussing the potential for AI to be used for harmful purposes. Leaders are encouraged to guide AI development toward positive outcomes and ensure that its applications are morally sound.

💡ERP (Enterprise Resource Planning)

ERP refers to software systems that help organizations manage business processes by integrating various functions such as finance, supply chain, and human resources. The video discusses how AI and Gen AI are being incorporated into ERP systems to improve efficiency, such as through predictive maintenance and supply chain optimization. These advancements are seen as beneficial for companies looking to modernize their operations.

💡Predictive Maintenance

Predictive maintenance is the use of data and AI to predict when equipment will fail, allowing for repairs before breakdowns occur. In the video, this is highlighted as one of the positive applications of AI in industries like manufacturing. AI agents could analyze data, forecast potential issues, and suggest maintenance actions, reducing downtime and improving efficiency.

💡AI Agents

AI agents are systems that can act on behalf of a user to perform tasks autonomously. The video mentions AI agents as tools that could handle tasks such as analyzing data and raising orders in manufacturing, thereby reducing the burden on human workers. These agents are seen as a way to increase efficiency by automating routine or complex tasks.

💡Legacy Systems

Legacy systems are older software or hardware systems that are still in use but may no longer be efficient or compatible with modern technologies. The video touches on the challenges of keeping these systems operational while integrating new AI and composable solutions. The need to modernize legacy systems is discussed as a hurdle for companies looking to adopt AI-driven processes.

💡Composable Solutions

Composable solutions refer to a modular approach to software development, where systems are made up of interchangeable and independent components. In the video, composable solutions are mentioned as a way to integrate AI into business systems more efficiently, allowing companies to adopt new technologies without overhauling their entire infrastructure. This approach is particularly useful for enabling features like predictive maintenance and fraud detection.

💡Fraud Detection

Fraud detection involves using technology to identify and prevent fraudulent activities, particularly in finance and security. In the video, AI is discussed as a tool that can help detect fraud in ERP systems by analyzing vast amounts of data and identifying suspicious patterns. This is one of the many practical applications of AI that can provide immediate benefits to businesses.

Highlights

Discussion on how technology and computers have changed basic skills like calculating change.

Mention of AI taking over certain decision-making processes, referencing 'The Terminator' and predictions about AI in the future.

The potential for AI in healthcare, emphasizing the importance of directing its use for good.

Concerns about AI misuse, particularly in cybersecurity where organizations have been compromised by hackers.

Judith’s view that technology must be guided by morals and ethics to be used for the right purposes.

Discussion of AI's dual nature: generating beneficial results and the potential for harm if misused.

Introduction of the concept of 'Gen AI' (generative AI) and how it differs from traditional machine learning.

The impact of generative AI on industries, particularly the ability to create synthetic data for business optimization.

Exploration of the concept of digital twins, especially in industries where safety and efficiency can be improved using AI-driven models.

The challenges of maintaining legacy systems while implementing AI and composable solutions for better modernization.

AI’s potential for predictive maintenance, supply chain optimization, and fraud detection, helping businesses be more efficient.

AI agents as a future tool, acting autonomously to carry out complex tasks and interacting more seamlessly with users.

AI agents' ability to analyze data, predict equipment failures, and even initiate actions like raising orders.

The evolving role of AI agents in supporting end-to-end processes in industries like manufacturing.

The ongoing need for humans to focus on higher-level business growth tasks while AI handles routine operations.

Transcripts

[Music]

we've all driven through a McDonald's

drive-thru and the person that's taking

your order is BET twist and between to

give you the correct change that's not

their skills anymore back when and I'm

aging myself back when I was a kid we

weren't allowed to use calculators in

school that was cheating right so we got

to be good at doing math in her head and

you know those flashcards and all those

different things today the skill set's

completely different um you know like I

said uh now thank goodness the computer

screen in front of that McDonald's

cashier tells them exactly give them two

quarters one nickel and one dime where

i' never get my change yeah so so mean

do you think that in the future then

we're going to be kind of told by AI

what to do because we're being told by

computers in a sense what they do gain

aging myself 1984 the classic movie The

Terminator uh what did we all learn from

that that in the year 2028 I think it is

that's four years from now that we're

all going to be taken over by robots and

and they're all going to be our armies

so we'll see how that goes to yeah we

already have drones that

are yeah they're coming yeah so uh

Judith any thoughts on on that regard of

good bad other U kind of what you're

seeing in the space or how you seen

people take it so like with any

technology we have the opportunity to

make it good or bad bad and we as to

leaders and as humans I think we need to

influence and make it work for good so

we can see a lot of applications uh you

know in Erp and I can see from my

Healthcare colleagues talk talk about

how much it can help in healthcare and

all that stuff so as long as we direct

that energy in the right places and make

the investment in the right places let's

ensure it's making it for you know it is

used for good and also with the

challenges that we have have there is

always a chance of Technology not being

used for the right reason but again

comes to morals and the ethics and also

the thought leadership in guiding the

technology to the right right places

have the investment where it needs to

be

yeah yeah so um I like it but then I'll

change the question a little bit for

nand then and put them on the spot so

same thing good bad other yet are we

okay with some of these companies open

AI Google

anthropic uh Amazon you know they're the

ones driving this right they're driving

this we're not driving this humans

aren't driving this like although the

humans that these companies driving this

these companies are very hierarchal

so yeah so no yeah I mean I think it's

still humans driving it and like Judith

said I I agree with Judith you know it's

up to people to and it's it's it's

people who will either use it for the

good or for the bad and I'm sure there

will be people who will use it for bad

but at the end of the day I I as the

history has shown people who have done

it positively far outweigh the negative

outcomes and so that's what I'm hoping

for AI too and I think that's what we'll

see with

AI okay yeah I mean then there's the bad

side right which is we saw was a health

one of the health care organizations you

know got encrypted and then paid the

ransom and then we see other ones paying

the ransom and then we have a lot of bad

coming potentially and it's being

utilized by gen and being utilized by I

think that quote unquote like script

kitties is what we call them like back

in the day like these people that take

something from somebody else that is a

really good hacker and then they go redo

the same thing so there's a lot of a lot

of bad coming and so the reason why I

asked the question about good bad or

other right is and how people are taking

it is because the fact that when it does

come to the bad where we see like these

large action models that are going to

come in and kind of do some of this when

it's bad people get scared and so when

people get scared they tend to withdraw

and if they withdraw from using

something that's effective or impacting

them or or going to actually enable them

to do more there's risk right and so um

so yeah so good bet other Ronald any

anything on that yeah so I think we need

to also make a difference between gen Ai

and AI right so AI is more is more uh

learning you know machine learning uh

going through Mass amounts of data to do

things with but gen generates text

generates voices generates images

generates fate right and and danger prob

so I think we when we when we continue

to talk about AI in

er um you know bad things

uh yeah we Tred to sell it so we we're

not we're not automatically thinking

much about the the worst things or the

bad things um yeah I I do do see a lot

of positive things just for AI in in Erp

if we talking about that with geni I

think we talking about a little bit

different things so this the the data

can be manipulated data can be resulted

and can be Pro processed back to to

people um and then then make mistakes

and make make errors in whatever they

are doing with thep system

so um so i i i t a little bit more to F

focus on the on the positive side of AI

at the

moment yeah that's great I mean that's

what we should be doing right so we

should be involved and having those

conversations like what are the

positives what are the gains and so so

and definitely the difference between Ai

and gen and gen especially creating

synthetic data and whatnot but on on top

of synthetic data are we seeing you know

some wins there in the Erp space so if

you have data there and you're working

with it kind of like what they say about

like digital Twins and whatnot like what

if you could create synthetic data that

is going to drive that Industry Drive

your business Drive the companies that

are utilizing this stuff to better

understand themselves because maybe you

have a synthetic Europe version of

itself like what does what does that

look like how how do you how are you

guys leveraging some of this technology

the digital twin itself um I haven't

seen really any digital twin in an e

personally in an e space um we have

enough trouble with keeping the old Eep

systems up and running and and think

about implementing a second one let

alone have digital Twins doing it but

you know the digital twin idea and with

all the II that you can can embed in

that is is fantastic I mean I have been

involved with an

a project that is looking

into modeling uh different factories

from different companies and and allow

allow them to to go into their own uh

Factory which is at a digital trim to

make optimizations to their own

processes and that and and and in

introduce more Ai and AI robots so that

they can indeed process people out but

this is more uh a long-term process in

an industry that is dangerous an

industry that is maybe also harmful in

some ways like like a health perspective

um and and I see great opportunities

there and and we we were very excited

about that that particular project um

so uh yeah I think that is that's just

where I want to leave it for now that

that I think that the there I see the

better opportunities for for some of the

uh the things that do really buil the AI

but what I if let's go back there for a

second about my comment about keeping

old Legacy systems running and

implementing new Legacy new systems it

will become Legacy at one

point you where we where we can be more

busy with composable Solutions and the

composable solutions have more AI

included in it and that will help

customers to do predictive maintenance

we do supply chain optimization uh

helping security and fraud detection

um all kind of different areas that that

they can uh modernize really quickly uh

as an as a microservice embeded of AI

and and bring more and somebody else

mentioned I think Andy that bring bring

more knowledge to their users to their

workers um yeah at a critical moment you

know

so yeah just to jump in there so I mean

that's a lot of good points and and on

that topic Ronald I was actually maybe

pull an n and to talk about how do how

do you see agents driving a lot of the

stuff that Ronald just described right

do do you see that coming in the future

Nandan yeah and thanks for the question

so AI agents is one area I'm really uh

looking forward to uh so the way to look

at AI agents is an agent working on your

behalf carrying out actions right uh so

like the predictions that you talked

about so basically you are so the way we

are doing things with a chat bot right

now or like an open AI chat GPD is we

are asking it questions and then we

going out and carrying out the actions

like you know if you're writing a email

you probably ask for it suggestions and

then you know copy pasting it somewhere

or the predictions you're looking at

looking it up and then you know uh doing

things uh in outside but with an AI

agent you have different agents so you

have an agent who will help you research

all this things about manufacturing you

can have another agent which will look

at all these analytics and give you this

different perspectives uh and and so you

know the AI agents can also then carry

out action so let us say that uh in

manufacturing uh it's uh it is able to

look at your uh data and it predicts

that some equipment is going to failure

right uh and then what it can do is that

okay this equipment is going to failure

it can even raise an order and give you

a draft order and tell you that you know

see this equipment this particular

spindle is going to fail in uh 10 days

you know do you want to raise an order

uh so that kind of things it can not

only uh interact with you chat with you

but it also it can carry out actions it

can do an end to end things uh so that

AI is much more

useful so that's my yeah take agents

helping

manufacturing yeah I think it's good

good to point that out because talking

about you know digital twins talking

about where data runs and then talking

about how that data can move especially

from either Legacy or non-legacy or just

from one system to another you know we

have to find as practitioners and as

people that are driving this is like how

do we how do we Define it how do we how

do we drive it forward and how do we

build that context into it so that the

end user is more Savvy or it's more ease

of use or they don't have to tell change

and count change back they just know

exactly what needs to happen to Andy's

Point earlier it's just like we need to

know what to do when to do just to do

that function because there's other

major things that we need to be working

on the business is continually to grow

uh this is where jobs aren't going to go

away in that sense because there's

always more work to do and so in that

side that that's where I kind of wanted

to drive it to to get to that point