Will AI adoption in ERP be a positive or negative, overall?
Summary
TLDRThe 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
🍟 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.
🤖 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.
💻 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.
Mindmap
Keywords
💡AI (Artificial Intelligence)
💡Gen AI (Generative AI)
💡Digital Twins
💡Ethics in AI
💡ERP (Enterprise Resource Planning)
💡Predictive Maintenance
💡AI Agents
💡Legacy Systems
💡Composable Solutions
💡Fraud Detection
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
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