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Discover how agentic AI is transforming businesses! Hosted by lowtouch.ai, the Agentic AI Podcast dives into real-world applications, success stories, and expert insights on no-code automation, enterprise AI adoption, and the future of intelligent agents. Perfect for CXOs, innovators, and tech enthusiasts looking to stay ahead in the AI era.
In today's business world, it often feels like, well, we're constantly being asked to do more with less. Streamline operations, slash costs, scale efficiently, and somehow do it all without adding a single person to the team.
Speaker 2:It's a huge challenge.
Speaker 1:Absolutely. Especially with just the sheer volume of information flooding us daily. But here at the deep dive, our mission is really to cut through that noise, give you a clear shortcut to understanding these complex game changing topics. Today, we're diving deep into the leading AI tools that aren't just, you know, automating tasks, they're fundamentally transforming enterprise operations as we speak. So if you're navigating the landscape of enterprise AI automation, maybe you're a seasoned enthusiast or perhaps a decision maker looking to drive strategic change, this deep dive is, essential knowledge for you.
Speaker 1:Okay. Let's unpack this.
Speaker 2:And it's a critical unpack. Absolutely. What's fascinating, think, is that despite really significant investments in AI across the board, many enterprises are still grappling with how to translate those investments into well, tangible, measurable value. There was actually an insight from data robot in 2024 highlighting that only about a third of AI teams genuinely feel equipped to meet their core business objectives.
Speaker 1:Wow. Only a third.
Speaker 2:Yeah. So the promise of this new wave of AI tools is precisely to bridge that gap, offering robust enterprise grade solutions designed to boost productivity and automation where it's, you know, truly needed.
Speaker 1:That statistic is pretty stark, isn't it? Really highlights that just buying AI software isn't enough. It's all about how you apply it. So to kick us off, we're gonna dive into what we're calling the foundational tools. These are the powerhouses of task automation that streamline workflows across different systems.
Speaker 1:Think of these as the digital workhorses tackling those repetitive manual tasks that, traditionally bog down operations.
Speaker 2:They're essential because they lay the groundwork. I mean, you can't run before you can walk. Right? And these tools automate the walking for you.
Speaker 1:Exactly. First up, let's talk about Zapier. It's become almost, you know, synonymous with basic task automation, but its enterprise features are really quite something. What it does is incredibly powerful. It connects over 8,000 different applications.
Speaker 1:Think CRMs, email, project management
Speaker 2:Thousands. Yeah.
Speaker 1:To automate those repetitive tasks. And for enterprises, it comes with robust features like role based permissions, audit trails, making it trusted by millions for secure and scalable automation.
Speaker 2:And what's often overlooked, I think, with tools like Zapier in enterprise context Yeah. Is the strategic impact of that simple automation. Yeah. You mentioned a multinational bank case study earlier, right? Where they use Zapier to automate their sales pipeline.
Speaker 1:Yeah. Reducing manual data entry.
Speaker 2:Exactly. And achieving a staggering three zero four per 4% ROI with what was it? $19,000,000 in additional revenue. Yeah. It's not just about cutting costs.
Speaker 2:It's about freeing up highly skilled sales professionals to focus on building relationships, complex negotiations, strategic outreach, stuff humans are good at rather than tedious data entry. That's where those really impressive ROI figures truly come from, reallocating human capital to higher value activities.
Speaker 1:That makes perfect sense. Okay. So if Zapier is the go to for many, what about enterprises needing even more control? Or maybe those with unique security needs? That brings us to N8N.
Speaker 1:It brings a sort of interesting twist to automation because it's open source. What's the core appeal of being open source in this space?
Speaker 2:Well, appeal of open source, especially for tech savvy enterprises and IT departments, it's really about the unparalleled flexibility and control. N8N offers both no code and code based options.
Speaker 1:Ah, so you can choose.
Speaker 2:Exactly. You can tailor it exactly to your needs. Plus it boasts advanced permissions, single sign on, which is, you know, crucial for large organizations, and even air gapped deployments.
Speaker 1:Air gapped deployments. Could you quickly unpack that for listeners who might not be familiar? What does that really mean?
Speaker 2:Absolutely. So an air gapped deployment essentially means the system can run completely isolated from external networks. No internet connection, nothing.
Speaker 1:Okay.
Speaker 2:This is absolutely paramount for organizations with the highest security and compliance requirements. Think defense, maybe finance, highly regulated industries where even a tiny vulnerability could be catastrophic. It's like having a digital fortress for your data.
Speaker 1:Got it. Secure.
Speaker 2:Very secure. A fantastic example is Stepstone, the job board. They leveraged an AAN to manage over 200 mission critical processes and they achieved 25 times faster integration times.
Speaker 1:25 times faster.
Speaker 2:Yep. That's not just a technical win. That translates directly into say accelerated time to market for new job features and faster responses to what competitors are doing.
Speaker 1:That's a massive leap. Okay. And rounding out this foundational section, we have Make, which people might remember as Integriment.
Speaker 2:Right. The rebrand.
Speaker 1:Yeah. So this is another low code platform, but it's specifically designed to scale with enterprise needs. What makes Make stand out for those large organizations, maybe with diverse tech stacks?
Speaker 2:Make really focuses on providing the tools for complex, scalable workflow automation. It emphasizes enhanced security, comprehensive analytics dashboards, and dedicated support, all things that are crucial for large organizations juggling lots of systems. When enterprises use Make to integrate, say, marketplace data sources, they're seeing similar gains to the AniDan example, like 25 times faster integration compared to doing it all with traditional coding methods. Wow. It means your IT teams aren't bogged down writing custom scripts for every single integration.
Speaker 2:They can build robust, scalable connections much more rapidly.
Speaker 1:What's really fascinating here is how these foundational tools address that immediate need for efficiency, right? They lay the groundwork, as you said, for more advanced intelligent automation within an enterprise.
Speaker 2:Exactly. By streamlining these core repetitive tasks, they free up significant resources, time, people, budget, and really set the stage for much bigger transformations down the line.
Speaker 1:Totally. And speaking of bigger transformations, here's where it gets really interesting. We're now moving into the next exciting frontier, dedicated AI agents. These bring intelligence directly into business processes. This isn't just about following fixed rules anymore.
Speaker 2:No. It's a big step up.
Speaker 1:It's about AI that can truly understand, interpret, and importantly, act.
Speaker 2:Yeah. Think of it this way. Simple automation, like Zapier or Make, is maybe like a well programmed robot following a very fixed instruction set. Do this, then do that. An AI agent is more like a skilled apprentice.
Speaker 2:It can learn. It can adapt. It can make decisions within a broader context even when it encounters, you know, unforeseen situations or natural language commands.
Speaker 1:That distinction is absolutely key. Leading the charge here is lowtouch.ai. Now this platform offers a suite of no code AI solutions specifically designed to enhance enterprise productivity. Their AI agents like, InvoFlux automate complex work flows in areas like finance, IT, operations, and they integrate seamlessly with existing ERP systems.
Speaker 2:That seamless integration is vital.
Speaker 1:Definitely. But what's also interesting is how they tackle the user facing side of AI with something called Prompt Stash. Tell us about that.
Speaker 2:Yes. Prompt Stash is really interesting for consistency and team collaboration. It's a Chrome extension basically that streamlines how you manage AI prompts across all the popular platforms. ChatGPT, Perplexity, Grock, Claude, Gemini, you name it.
Speaker 1:Okay. So managing the prompts themselves.
Speaker 2:Exactly. It allows teams to efficiently create, organize, and deploy their prompt templates. So everyone's using the best approved prompts, ensuring consistency, and saving a ton of valuable time. For enterprises, this means you get these plug and play AI solutions for automation and AI driven productivity, all without needing deep coding expertise.
Speaker 1:Makes sense.
Speaker 2:A great real world example. A financial services company used InvoFlux to automate compliance reporting. They reduced manual effort by 70% and ensured critical GDPR and IPA compliance. Separately, their marketing team used Prompt Stash to maintain a central library of prompts for social media content. That ensures brand consistency and saves significant time on content creation.
Speaker 2:It empowers different departments in different ways.
Speaker 1:That's a powerful combination. Automation on the back end, prompt management on the front. Okay. Next up, Adept. Adept builds AI agents designed to automate software processes using natural language instructions.
Speaker 1:What kind of problem does that solve, especially for companies with complex, maybe even older legacy systems?
Speaker 2:It solves the problem of needing to write custom code for every single new automation you want to create, which as you can imagine is slow and expensive. What this means for you, the user, is the ability to quickly set up complex workflows just by describing what you want in plain English without needing traditional coding.
Speaker 1:Just tell it what to do.
Speaker 2:Pretty much, yeah. It's particularly helpful for enterprises dealing with custom built or older legacy systems that need to automate specific tasks like, say, intricate data extraction from various unstructured documents or websites. Adept's AI agents are already automating workflows, like checking shipping availability across hundreds of different supplier sites, ensuring both accuracy and efficiency at scale. This kind of agentic capability, as it's sometimes called, moves AI beyond simple, rote task execution to truly intelligent agents. They understand natural language, they interpret context, they manage complex multi step workflows.
Speaker 2:It represents a really significant leap in how businesses can leverage AI, allowing for far more sophisticated and adaptive automation than ever before.
Speaker 1:That's a crucial distinction, the agentic part. And that's a perfect segue into our next category, which is all about how AI directly enhances human productivity and transforms customer interactions. It's really about amplifying human potential, isn't it, rather than just replacing tasks.
Speaker 2:Precisely augmentation, not just automation.
Speaker 1:Let's start with Notion AI. Now many people use Notion for notes and collaboration. This tool embeds AI features directly within that Notion workspace. So you get features like meeting transcription, content generation translation, advanced search, all built right into your collaborative environment. But for enterprise users, what's the big win in terms of security?
Speaker 1:That's always a concern.
Speaker 2:Yeah. Always. The big win for enterprise security with Notion AI is their zero data retention policies.
Speaker 1:Okay. What does that mean practically?
Speaker 2:It means any data processed by their AI isn't used to train their models or stored beyond the immediate processing needed for the task. Which is a huge comfort obviously for companies dealing with sensitive information and strict compliance rules like GDPR or IPA. So this helps teams and enterprises enhance collaboration, streamline documentation, automate knowledge management, all more securely. We've seen enterprises use Notion AI to transform raw meeting notes into structured project plans or translate documents instantly for global teams saving hours and hours of manual work. I remember spending hours manually transcribing meeting notes myself wishing there was an easier way.
Speaker 2:This Right. This would have been a godsend back then.
Speaker 1:Oh, I can absolutely relate to that. Then there's fireflies.ai, another AI powered meeting assistant. It transcribes, summarizes, analyzes your meetings integrating seamlessly with platforms like Zoom, Microsoft Teams, Google Meet.
Speaker 2:Usual suspects.
Speaker 1:Exactly. Who benefits most from this kind of meeting intelligence?
Speaker 2:Well, support teams are huge beneficiaries. Managers, executives too. Really, anyone who needs to capture meeting insights without the soul crushing manual effort of note taking will find it invaluable. Think about support teams using fireflies.ai to automate their note taking during customer calls. It frees up valuable time for them to do more value added activities like actively listening, showing empathy, solving the actual problem, ultimately improving customer interactions.
Speaker 1:Less time typing, more time connecting.
Speaker 2:Exactly that.
Speaker 1:And speaking of interactions, customer experience is such a critical area where AI is making massive waves. The next two tools are all about that space. First, let's look at Forethought. This provides AI powered customer support automation. How does it manage to instantly resolve common queries and intelligently triage tickets often without needing a human agent right away?
Speaker 2:Forethought uses quite sophisticated AI to understand the intent behind customer queries. Right. Much like a very smart, very fast human agent would. It's trained on past interactions and knowledge bases. So it's designed to instantly resolve those common repetitive questions, where's my order?
Speaker 2:How do I reset my password? And intelligently triage the more complex tickets, routing them to the right human agent with context.
Speaker 1:So it handles this simple stuff fast.
Speaker 2:Right. It's ideal for customer support teams looking to significantly reduce ticket volumes and improve those first response times. We saw one company using Forethought achieve an impressive 80% ticket deflection rate.
Speaker 1:8080%.
Speaker 2:Meaning 80% of incoming queries were resolved entirely by AI without needing a human agent. And crucially, they maintained a four point zero CS ATS score.
Speaker 1:Wow. So quality didn't suffer?
Speaker 2:Exactly. It shows you can dramatically reduce agent workload and maintain high service quality. It's not always a trade off.
Speaker 1:That 80% deflection rate is incredible. Okay. And finally, in this section, we have Intercom. Many know Intercom for its chat features. Its fin AI agent is adept at handling complex customer queries and integrates with existing help desks like Zendesk and Salesforce for seamless support experiences.
Speaker 1:Where does Intercom's strength lie, particularly when queries get a bit more complex?
Speaker 2:Intercom's strength, I think, lies in its ability to handle more nuanced, multi turn conversations and its deep integration into the existing customer support ecosystem. It's not just a standalone bot. This empowers enterprises to provide instant, high quality customer answers even for slightly trickier questions, again with minimal human intervention needed for many cases. Enterprises are using Intercom's FinAI to automate responses to a wide range of common queries, which again improves response times drastically and allows human agents to really focus their energy on the more complex, sensitive, or empathetic issues that truly require that human touch.
Speaker 1:This really brings up an important question, doesn't it? How do these AI tools not just, you know, replace tasks, but truly transform our daily work and our customer interactions? What's the bigger picture emerging here?
Speaker 2:Well, bigger picture, I believe, is that by taking over the routine, the repetitive and the easily answerable tasks, these AI tools allow human teams to focus their skills on higher value activities. We're talking about the tasks that demand creativity, critical thinking, empathy, strategic planning, complex problem solving. Things AI isn't great at yet.
Speaker 1:But uniquely human skills.
Speaker 2:Precisely. It's about augmenting human capability, making our work potentially more meaningful and impactful, not just automating it away entirely.
Speaker 1:That's a crucial distinction to keep in mind. Okay. And now for our final category, we're shifting gears slightly to talk about how advanced AI is becoming the backbone of data driven strategic decisions. This isn't just about day to day efficiency. It's about gaining a real competitive advantage.
Speaker 2:Absolutely. We're moving from just reacting to past data to actively predicting and even shaping the future based on it. This is a fundamental shift.
Speaker 1:And this brings us to DataRobot. DataRobot enables businesses to build, deploy, and manage both predictive and generative AI models at scale. We're talking about critical use cases like predicting customer churn, deeply understanding customer behavior, getting accurate demand forecasting, things that directly impact the bottom line. Who is this tool really for? It sounds pretty advanced.
Speaker 2:It is quite sophisticated, yes. It's primarily aimed at data science teams and organizations that need advanced capabilities for serious data driven decision making across various industries. Remember that multinational bank example we discussed earlier with Zapier? Well, that same bank also used DataRobot to optimize its operations.
Speaker 1:Ah, interesting.
Speaker 2:And they achieved that impressive 304% view ROI and $19,000,000 in additional revenue, specifically through the AI models they built and deployed using DataRobot driving strategic optimization. This isn't just about automating an existing report, it's about leveraging vast data sets to maybe identify entirely new revenue streams or dramatically reduce future risks like fraud or churn. They're predicting what will happen, not just reporting what did happen last quarter.
Speaker 1:Right. That shift from reactive to proactive is huge. What's fascinating here is how these tools empower enterprises to make that leap. By leveraging vast datasets and these sophisticated AI models, organizations can predict trends, anticipate challenges, identify opportunities with the precision that was frankly unimaginable just a few years ago.
Speaker 2:Totally unimaginable.
Speaker 1:And this capability provides a significant competitive edge, allowing businesses to adapt and innovate at a much, much faster pace.
Speaker 2:Absolutely. Speed and foresight.
Speaker 1:So we've explored 10 really incredible tools here today. But drilling down, what does all this mean for you, the decision maker listening or the AI enthusiast, looking to actually adopt to these powerful tools in your own enterprise? What are the common threads that make these tools and others like them truly suitable for large organizations beyond just the features?
Speaker 2:That's the real strategic question, isn't it? Because these AI tools aren't just powerful, they're generally built with specific enterprise needs in mind. Firstly, security is absolutely paramount. You'll see robust features like strong data encryption, role based access controls, compliance certifications for GDPR, I pay SOC two and so on. Ensuring your data is protected is table stakes.
Speaker 1:Non negotiable.
Speaker 2:Completely. Secondly, scalability is key. These platforms are built to handle immense data volumes and growing numbers of users. They need to grow with your business without hitting performance bottlenecks or breaking the bank.
Speaker 1:Right. Can't outgrow it in six months.
Speaker 2:Exactly. Thirdly, integration needs to be seamless. These tools usually offer compatibility with your existing core systems. Your ERP, your CRM, your help desk software. Smooth adoption relies on playing nicely with what you already have, not forcing a rip and replace.
Speaker 2:And finally, support is critical at the enterprise level. Enterprise plans almost always include dedicated support managers, service level agreements, SLAs, account management, and often advanced features like single sign on SSO for easier user management and identity control across the org. So for the CTOs, the operations leaders listening, smart adoption really comes down to a few key tips I think. First, identify the real pain points. Don't just implement AI for the sake of saying you have AI.
Speaker 2:Focus on specific, measurable, repetitive or inefficient processes where AI can genuinely make a difference. Think manual data entry, complex prompt management for teams, slow customer service responses.
Speaker 1:Mind the actual problem first.
Speaker 2:Precisely. Second, pilot projects are your best friend. Test these tools and controlled environments first. Validate their impact, try to calculate a realistic ROI before you commit to a massive full scale deployment. That minimizes risk and helps build internal confidence and buy in.
Speaker 1:Start small, prove value.
Speaker 2:Exactly. Third, train your teams. This is so often underestimated. Invest in comprehensive training to ensure effective adoption and actually maximize the productivity gains you're hoping for. Without proper training, even the best tools can fall flat or cause frustration.
Speaker 2:Effectively. Absolutely. Fourth, measure ROI continuously. Don't just measure it for the pilot, keep tracking key metrics, efficiency gains, cost reductions, improvements in customer satisfaction, employee satisfaction, even to quantify the ongoing value delivered. This helps justify the investment and secure budget for future initiatives.
Speaker 1:Keep proving the case.
Speaker 2:You got it. And finally, perhaps most importantly, Governance. Establish clear policies for ethical AI use, data privacy, and regulatory compliance right from the outset. This isn't an afterthought you bolt on later, it needs to be foundational to responsible and sustainable AI adoption. If we connect this all back to the bigger picture, it's really about taking a holistic approach.
Speaker 2:It's not just about adopting individual point solutions but integrating them into a cohesive strategy for intelligent automation and driving sustained digital transformation across your entire organization.
Speaker 1:Wow. What an incredible journey we've taken today, really. From those foundational task automation tools like Zapier, NN, and Make the One streamlining core operations
Speaker 2:Building the base.
Speaker 1:To the intelligent AI agents transforming business processes with low touch dot AI and Adept acting like those smart digital apprentices we talked about. Then moving on to the team productivity enhancers like Notion AI and Fireflies dot AI, just making our daily work lives that bit smoother.
Speaker 2:Definitely needed.
Speaker 1:Then we explored the innovators in customer support with Forethought and Intercom, really revolutionizing how businesses connect and interact with their customers. And finally, touching on the powerful data processing capabilities of DataRobot, driving that strategic proactive decision making. These 10 solutions and others like them are truly reshaping the enterprise landscape right now, offering scalable, secure ways to boost productivity and automation. The immense value for you, the listener, in really understanding this rapidly evolving space cannot be overstated.
Speaker 2:I agree. And I think the real power ultimately lies not just in the individual capabilities of any single tool, but in how they can be strategically combined and integrated together. It's about fostering a culture of intelligent automation within an organization, where eventually every process, every decision can potentially be enhanced by AI, leading to a more agile, more competitive, and maybe even a more human centric enterprise in the long run.
Speaker 1:Absolutely. A powerful thought to end on. So as you go about your day today, I want you to consider just one significant pain point within your own organization. Maybe it is that soul crushing manual data entry or the endless meeting follow ups that just drain your team's time or perhaps those repetitive customer queries that constantly swamp your support team. Just imagine the potential ripple effect that a single well chosen AI automation tool could have on that specific problem?
Speaker 1:What's maybe the first small step you might take to pilot that change? Something to think about. Thank you so much for joining us on this deep dive into enterprise AI automation.