AlignAI

?? We’re excited to announce the redesign of our product page, showcasing four key areas that highlight how companies are using the AlignAI platform today: ?? AI Center of Excellence ?? AI Lifecycle Management ?? AI Tool Enablement ?? Data Governance & Quality See how we’re making it easier for your company to change the way you build and adopt #AI. AlignAI Website: https://lnkd.in/gtyD7rSg #AICOE #DataGovernance #technology #strategy

Centralization is the key to data & AI governance in this week's #TunebackTuesday ?? ?? Episode 3: Is MLOps Just Hard Mode for Data Engineering? In this clip, we hear our Co-Founder & CPO, Brendan Kelly, elaborate on the importance of centralized organizations. Brendan suggests that organizations should have a method in place that allows teams to remain relevant and updated on the latest data & AI governance frameworks both internally and externally. Stay tuned for next Tuesday, where we'll post another clip & revisit another important topic around Data and AI. ?? Watch Episode 3: https://lnkd.in/guP5T9tn AlignAI Website: https://lnkd.in/e4niChAP #tech #strategy #data #AI

Just attended the first keynote session at the Data Science Symposium 2024 with Rehgan Bleile (Avon), Co-Founder & CEO of AlignAI ??? Her talk, “From Models to Agents: The Evolution of Data Science and AI”, provided a fascinating dive into the past decade’s advancements in AI. Rehgan highlighted the critical shift from traditional machine learning models to more advanced AI systems, covering everything from architecture changes and security challenges to the growing importance of open-source tools and risk concerns. The future of AI is bright—and complex. Looking forward to exploring these topics more throughout the symposium! ??

?? We're uncovering strategic AI execution in this week's #TunebackTuesday ?? Episode 11 - AI in 2024: Emphasizing Execution In this clip, we explore how companies are strategically managing AI adoption: ? Mass Adoption with Low Investment: Companies introduce AI solutions as a low-risk, low-investment opportunity, making it easier for employees to engage with the technology and see its benefits firsthand. ? Balancing Build vs. Buy: The discussion highlights the importance of understanding value attribution, whether companies decide to build custom AI models or buy existing solutions, ensuring they see measurable returns from these investments. Stay tuned for next Tuesday, where we'll revisit another important topic around Data and AI. ?? Episode 11: https://lnkd.in/eipTVgea AlignAI Website: https://lnkd.in/e4niChAP #AIstrategy #AIadoption #digitaltransformation #GenAI

?? We're uncovering the hurdles companies face in adopting AI in this week's #TunebackTuesday ?? Episode 15 - A UX Perspective on AI In this clip, we break down two key challenges enterprises face when adopting AI: ? Identifying game-changing use cases unique to their business ? Managing risk with proper guardrails in place to prevent issues from occurring Stay tuned for next Tuesday, where we'll revisit another important topic around Data and AI. ?? Episode 15: https://lnkd.in/gvsSXuxh AlignAI Website: https://lnkd.in/e4niChAP #AI #usecases #strategy #AIadoption

Our September newsletter is here! ?? Don’t fall behind—see what the team at AlignAI has been up to lately with webinars, podcasts, conference insights, and upcoming keynotes???

?? Join our Co-Founders, Rehgan Bleile (Avon) and Brendan Kelly on September 26th as they discuss how enterprises are building trust and driving real value with AI. Learn about the emerging trends shaping AI adoption and its evolving role within enterprises. ?? #AI #AIAdoption #AITrends #EnterpriseAI

?? We're addressing enterprise AI security concerns in this week's #TunebackTuesday ?? Episode 8 - AI Strategy & Governance In this clip, we break down the top concerns enterprises have around #AI security: ? Transparency of AI models—unclear reasoning behind decisions sparks governance challenges ? Data security—uncertainties around privacy and how sensitive information is managed Stay tuned for next Tuesday, where we'll revisit another important topic around Data and AI. ?? Episode 8: https://lnkd.in/exsAvPhB AlignAI Website: https://lnkd.in/ebJ6rEkm #AIsecurity #GenAI #AIgovernance #strategy

I have been having a lot of discussions on how real this major SaaS replacement using AI is for Klarna. And if so, how replicable is this? As mentioned on this last week's episode of All In, Chamath Palihapitiya talks about how the industry historically "never went after the system of record" software, like Salesforce or ERPs. They are too hard to rip and replace. Now we are hearing from Klarna that they have managed to do this with AI. Systems of record have a REALLY low tolerance for being wrong, especially in regulated industries. How much custom work is required to get AI to generate accurate enough results to do this? These systems are notoriously complex. They require A LOT of training for admins to maintain, and even then it is a struggle. Each implementation is different. Consulting firms make TONS of money customizing instances of this software to make it work for companies. Now Salesforce is shifting gears to enable their customers to build agents themselves with Agentforce. What does this mean for their underlying software? Did they see the writing on the wall? Many enterprises have leaned on SaaS to provide a framework to operate, automate, and collect/manage data (you tell us how to do it). These SaaS providers take usage and learnings across companies, build functionality, and deliver it across their customers. And they maintain it! Of course, there are some enterprises who think they know best and build their own. Then companies assign an owner of that system and the processes around it to coordinate efforts and make sure it is providing value (if they do it correctly). They are essentially relying on "what is everyone else doing?" combined with "who knows our business the best internally to make sure it works for us?" A downside (and upside) is that SaaS vendors are incentivized to generalize patterns (especially VC backed companies), so customization is usually always needed at large enterprises. If AI can build and maintain these systems, problem solved on that end of relying on external vendors to do it. If it can also solve the customization problem, even better!! However.... what happens when the knowledge sharing stops? The generalized patterns, although sometimes tough to customize, are also incredibly useful to introduce new frameworks and shifts in the way these enterprises operate. This is why Salesforce has been adopted across so many enterprises. It was a much better operating model than what they had before. This really begs the question of which parts will get open sourced and shared. Will the common patterns and frameworks just become freely available and the customization and maintenance will get automated by AI? "Software was eating the world, now it is eating itself". https://lnkd.in/gZ93bx-S

?? We are one week away from our webinar! Learn about the key factors behind successful AI use cases and how organizations can drive meaningful outcomes with AI projects and solutions. ?? Mark your calendar and join us virtually: https://lnkd.in/e-FM9UTw #AI #strategy #AIAdoption #AIUseCases