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From AI Hype to Real Business Results · Full Tech Ahead

• 0:19
  SPEAKER_01: Hello and welcome to Full Tech Ahead.
• 0:22
  SPEAKER_01: I'm your host, Amanda Razzani.
• 0:24
  SPEAKER_01: And with me today, I'm excited to be here with Mark Talbot.
• 0:28
  SPEAKER_01: He is AVP Customer Success AI Incubation at Appian.
• 0:33
  SPEAKER_01: How are you doing today?
• 0:34
  SPEAKER_00: I'm well, Amanda.
• 0:35
  SPEAKER_00: Thank you for having me.
• 0:37
  SPEAKER_01: Happy to have you on this show.
• 0:39
  SPEAKER_01: So can you share first a little bit about Appian and the services that you provide?
• 0:44
  SPEAKER_00: Right.
• 0:45
  SPEAKER_00: So at Appian, I focus on helping companies move AI from isolated experiments into governed production workflows.
• 0:53
  SPEAKER_00: So at Appian's core strength is process orchestration.
• 0:57
  SPEAKER_00: So my lens is always where does AI fit into real work in a way that's secure, measurable, and scalable?
• 1:06
  SPEAKER_01: Fantastic.
• 1:07
  SPEAKER_01: Well, we're going to jump right in today's topic: how organizations move beyond hype to deploy automation and AI in secure, scalable ways, particularly in complex regulated environments.
• 1:21
  SPEAKER_01: And I want to start with your collaboration recently with Harvard Business Review on some research around enterprise AI adoption.
• 1:32
  SPEAKER_01: Can you share more about that and some of the key takeaways?
• 1:36
  SPEAKER_00: Yeah, the research was interesting.
• 1:38
  SPEAKER_00: So one thing we found was 59% of organizations already have AI in production, but only 16% realize a high degree of measurable value from those investments.
• 1:50
  SPEAKER_00: So many companies are already using this to drive productivity at 64%, operational efficiency at 58%, but they're not seeing that impact on top-line business growth.
• 2:02
  SPEAKER_00: And one thing is interesting only 18% said AI is primarily integrated into workflows, which we believe that explains why many companies are struggling to receive impact from AI.
• 2:16
  SPEAKER_00: But if you look at the data carefully, organizations embedding AI directly into workflows are seeing stronger outcomes.
• 2:24
  SPEAKER_00: So 70% of those organizations reported moderate or substantial value from those efforts.
• 2:32
  SPEAKER_01: Yes, I think this is a struggle for many.
• 2:36
  SPEAKER_01: So let's let's talk about that.
• 2:39
  SPEAKER_01: What are some of the biggest barriers or roadblocks that you're seeing?
• 2:44
  SPEAKER_01: And what advice do you have to overcome those?
• 2:48
  SPEAKER_00: Right.
• 2:49
  SPEAKER_00: So typically they try to apply AI to broken or inefficient processes.
• 2:56
  SPEAKER_00: They're focusing too much on the technology and not enough on the implementation strategy.
• 3:01
  SPEAKER_00: So what they'll do is they'll underestimate governance, security.
• 3:05
  SPEAKER_00: I mean, some of the data quality challenges that are out there.
• 3:08
  SPEAKER_00: I mean, they'll treat AI as this standalone tool instead of part of an integrated workflow.
• 3:14
  SPEAKER_00: So, I mean, that's what we see.
• 3:17
  SPEAKER_01: Mm-hmm.
• 3:18
  SPEAKER_01: Well, I mean, we've seen an explosion in the AI space because of course it has rapidly advanced over the last few years.
• 3:26
  SPEAKER_01: And so now that we are hitting that um phase where organizations are looking for ROI and how to improve, where are they falling short and why?
• 3:39
  SPEAKER_00: Right.
• 3:40
  SPEAKER_00: So earlier on, 2024, 2025, we were focused on experimentation.
• 3:46
  SPEAKER_00: Now organizations need measurable business outcomes.
• 3:50
  SPEAKER_00: So executives are asking where AI is improving revenue, decreasing risk, and decreasing costs.
• 3:57
  SPEAKER_00: So I think what companies are doing is that they're becoming more strategic and selective with their AI investments.
• 4:03
  SPEAKER_00: So what it depends on now is that operational execution and just not the innovation that we got away with earlier on.
• 4:11
  SPEAKER_01: Do you think this is a big communication issue or a training issue or all the above?
• 4:18
  SPEAKER_00: I think it's all of the above.
• 4:20
  SPEAKER_00: I mean, I think part of it is a um communication issue.
• 4:25
  SPEAKER_00: So I think it's a lack of understanding of what those common barriers are.
• 4:29
  SPEAKER_00: So you'll have siloed data, you'll have lack of a data fabric that some organizations provide.
• 4:37
  SPEAKER_00: You'll have fragmented systems where you need to bring that data to the AI.
• 4:42
  SPEAKER_00: And there's also governance concerns, right?
• 4:45
  SPEAKER_00: You want to make sure you're able to act on that AI safely.
• 4:49
  SPEAKER_00: So really, when you start to execute on AI, I mean, what it requires is organizational discipline.
• 4:57
  SPEAKER_00: You need to have long-term planning on what you need to do to get AI approved within your organization.
• 5:04
  SPEAKER_00: So really, the most successful companies, what they're doing is they're taking a really intentional, organized and phased approach.
• 5:14
  SPEAKER_01: Okay.
• 5:15
  SPEAKER_01: Well, what separates companies that are seeing meaningful business value from AI, from those that are stuck in pilot mode?
• 5:24
  SPEAKER_00: Right.
• 5:25
  SPEAKER_00: So successful organizations start with clear business problems and measurable goals.
• 5:32
  SPEAKER_00: AI works best when embedded into workflows and existing operations.
• 5:37
  SPEAKER_00: So they'll take a workflow, they'll see areas that have a large amount of, I would say, unnecessary human toil, and they'll look at how AI can automate that work.
• 5:49
  SPEAKER_00: I think that involves cross-functional alignment with IT and the business and governance with your AI center of excellence.
• 5:58
  SPEAKER_00: I mean, I think that's really critical to scaling successfully.
• 6:03
  SPEAKER_01: I keep hearing that term a lot.
• 6:05
  SPEAKER_01: That's becoming really a popular term is the AI centers of excellence.
• 6:10
  SPEAKER_01: Uh, what kind of impact do you think is being made there?
• 6:14
  SPEAKER_01: Is that having a big impact, having these AI centers of excellence?
• 6:18
  SPEAKER_00: I mean, I think it is.
• 6:19
  SPEAKER_00: I think there's lessons learned when deploying AI.
• 6:23
  SPEAKER_00: I think there's certain questions you need to ask from a data governance perspective to make sure that your uh data is safe.
• 6:32
  SPEAKER_00: I mean, the last thing that you need in your organization is for you to make the headlines for the wrong reasons.
• 6:38
  SPEAKER_00: These AI centers of excellence also ensure that you have measurable business goals going into your AI application and you have measurable business outcomes to ensure it's successful.
• 6:52
  SPEAKER_00: So these organizations are going to ask, okay, well, how is it performing before you introduce AI?
• 6:57
  SPEAKER_00: How is it performing after AI was introduced?
• 7:01
  SPEAKER_00: What tools are you using to measure success?
• 7:04
  SPEAKER_00: How do you know the data is safe?
• 7:06
  SPEAKER_00: What type of logging are you doing?
• 7:08
  SPEAKER_00: What type of auditing are you doing?
• 7:11
  SPEAKER_00: What type of measurement are you doing?
• 7:13
  SPEAKER_00: So I think all those things your AI centers of excellence take into consideration.
• 7:20
  SPEAKER_01: Well, there at Appian, um, you probably have a lot of experience with this.
• 7:25
  SPEAKER_01: Um, how does governance, security, and workflow integration shape those successful AI deployments?
• 7:33
  SPEAKER_00: I mean, they're they're non-negotiable.
• 7:35
  SPEAKER_00: So one of the nice things about the Appian platform, the auditability is built in.
• 7:42
  SPEAKER_00: I would say the governance is built in if you're on cloud.
• 7:45
  SPEAKER_00: We have third-party auditors that come in ensure that we're, you know, SOC2 compliance, ISO compliant, FedRamp compliance.
• 7:52
  SPEAKER_00: And this is important to make sure that your data is safe.
• 7:57
  SPEAKER_00: And that's a part of the conversations when we're talking with these AI center of excellence.
• 8:03
  SPEAKER_00: They want to make sure that every interaction with the AI is audited so that they can see how their users are interacting with the AI.
• 8:12
  SPEAKER_00: They need that to make sure they can improve it.
• 8:14
  SPEAKER_00: They need to make sure that there's explainability and traceability to how the AI came to that decision.
• 8:21
  SPEAKER_00: So that's why it's it's useful to have that framework to ensure that you're doing that with every AI workflow that you're building.
• 8:30
  SPEAKER_01: Absolutely.
• 8:31
  SPEAKER_01: Well, looking forward, as we mentioned, AI is advancing so quickly.
• 8:37
  SPEAKER_01: What do you envision for the future of AI?
• 8:39
  SPEAKER_01: What's the next thing that business leaders need to be thinking about?
• 8:43
  SPEAKER_00: Yeah, I think there's going to be less focus on hype and model comparisons.
• 8:48
  SPEAKER_00: So less focus on am I using Claude or am I using some of the GPT models and more focus on those business outcomes, more focused on trust, more focus on governance, more focused on operational efficiency.
• 9:08
  SPEAKER_00: And I believe AI is going to be more embedded into existing workflows and systems, and there's going to be less focus on chatbot.
• 9:17
  SPEAKER_00: I mean, one of the things I've noticed is if you have AI chat and you have 10,000 employees, you have 10,000 different ways of doing things.
• 9:26
  SPEAKER_00: So that's one of the reasons why AI needs to be embedded into existing workflows.
• 9:32
  SPEAKER_00: And so I think what organizations are going to do is they're going to prioritize scalable and secure platforms over these disconnected chat tools.
• 9:42
  SPEAKER_01: Well, if there was one key takeaway you could leave our audience with today, what would that be?
• 9:48
  SPEAKER_00: I think it's going to be start with clear business challenge and measurable goals.
• 9:53
  SPEAKER_00: Focus on workflows where AI can drive operational improvements.
• 9:58
  SPEAKER_00: So I would say build governance and change management early.
• 10:01
  SPEAKER_00: And I would prioritize sustainable implementation and the long term rather than chasing every AI trend.
• 10:09
  SPEAKER_01: Okay, great advice.
• 10:11
  SPEAKER_01: Well, thank you so much for coming on the show and sharing your insights with us today.
• 10:16
  SPEAKER_00: Thank you for having me, and we'll talk soon.
• 10:18
  SPEAKER_01: All right.
• 10:19
  SPEAKER_01: And thank you to our audience.
• 10:20
  SPEAKER_01: If you have any questions or comments, leave those below, and I'll try to respond as soon as possible.
• 10:25
  SPEAKER_01: And until the next podcast, have a wonderful week.