Enterprise AI

Four Key Take aways from Impact24 by Tech Talk Summit

Circuitry.AI CEO, Ashok Kartham, shares his top four takeaways from the recent Impact24 event hosted by Tech Talk Summit.




TechTalk Summits held IMPACT 2024, an event dedicated to AI and the future of business, from Feb 5-7 in St Petersburg, FL. IDC analysts and other presenters have shared insights on various topics including Generative AI, AI use cases, AI infrastructure, AI governance, and more. 

We wanted to share the top four key takeaways from this conference.

The Economic value of generative AI is in trillions of dollars

As expected, almost every presenter referenced Gen AI. A few key stats and predictions that IDC analysts shared are:

  • GenAI will add nearly $10 trillion to Global GDP over the next ten years.
  • Enterprises will leverage GenAI and automation technologies to drive $1T in productivity gains by 2026.
  • By 2025, 35% of enterprises will have mastered the use of GenAI to co-develop digital products and services, leading to double the revenue growth compared to their competitors.
  • In a Survey by IDC, 9.6% responded that GenAI has already disrupted their business, 22.6% that it is starting to disrupt now, and 36.5% that it will have a significant impact in the next 18 months.

Ritu Jyoti, Group VP, AI, Automation, Data and Analytics, from IDC shared the top business benefits of GenAI:

  • Expanding labor productivity,  
  • Personalizing Customer Experience,  
  • Accelerating R&D, and
  • Emerging New Business Models

I think GenAI use cases must link to prioritized business outcomes.

Companies are establishing KPIs such as Consistent Customer Experience, Impacted Revenue, Cost Reduction, and Performance of IT Support to link to GenAI use cases.


GenAI use cases and benefits are real and numerous

Most organizations are still learning about generative AI and are trying to determine the most applicable use cases. IDC framework categorizes AI use cases into Productivity, Functional, and Industry use cases with increasing levels of maturity. Productivity use cases increase task productivity, drive operational efficiencies, and improve asset utilization. Functional use cases increased functional effectiveness and contextualized experiences. Industry use cases enable new digital business models, products, and services and industry-specific competitive moats.

It was particularly interesting what Vishal Gupta, CTO and CIO of Lexmark shared. Lexmark has not only realized internal benefits from AI but also created a new product offering, Optra, to provide IoT and AI applications to other manufacturers.

IDC analysts also shared the use case of CarMax driving business value with GPT to help make buying a used car effortless. You can read more about this case in a CIO article.

One of the short-term use cases in sales is product recommendations based on purchase history, buying behavior, and stated preferences.  

Read more about Circuitry.ai Product AIdvisor, which enables companies to help customers and sales teams with product knowledge and recommendations.

The top three reasons companies use generative AI:

  • Improve customer experience
  • Decision-making
  • Revenue generation

The framework to prioritize use cases can be mapped out using two dimensions: Complexity (Low-High) and Value (Low-High).


Decision Intelligence to enhance decision-making and decision velocity 

In addition to Gen AI, Chandana Gopal, Research Director, Future of Intelligence, at IDC, presented on "AI-Driven Decisioning: How AI can improve Decision Velocity." Chandana highlighted the problem that 82% have not been able to remove data silos, and 77% say data intelligence is a challenge despite over $290 Billion invested in 2022 on Big Data and analytics.

The Enterprise Intelligence architecture will have four planes: Data plane, Data Control plane, Data Analysis plane, and Decisioning Plane. She also shared opportunities to apply AI to elevate Decision Intelligence. A few of those opportunities are exploring insights using natural language, Making insights accessible to a wide range of users, and exposing knowledge and insights from unstructured data.  

Mickey North Rizza, Group Vice President, Enterprise Software at IDC, shared GenAI use cases by industry. According to Mickey, manufacturing organizations are focused on enhancing decision-making within operations, driving higher operational efficiency levels, and supporting digital customer engagement applications. Some emerging use cases include Augmented maintenance & knowledge management, Cognitive Asset Performance Management, and SLA Automation.

We are excited to see this focus on how Gen AI and other AI techniques can be applied to improve decision-making. Please read more on how Circuitry.ai is enabling companies to optimize business outcomes with decisions powered by AI.


Successful AI implementations require upgrading and scaling AI skills, infrastructure, and architecture

IDC Survey results have shown that security concerns are the most critical challenge with implementing GenAI initiatives, even above the cost, ROI, and skills concerns. All parts of the business are concerned with data and intellectual property challenges. Many strategies were shared to mitigate the risk, including proactively mitigating risks for the end-to-end software development process, establishing proven risk-mitigation actions for hallucinations, setting up data access controls and policy management layer, and establishing rigor for evaluation metrics.

Some of the advice to get started on Gen AI use cases include:  

  • Prioritize GenAI use cases according to business value, cost, and potential business risk.
  • Build the Generative AI Roadmap based on prioritized use cases.
  • Enable intelligence architecture based on a data-centric platform underpinning the enterprise.
  • Upgrade technology architecture and drive towards more composable architecture.
  • Have an upfront focus on trust and create a conducive environment for employees to thrive in an AI era.
  • Upskill the teams for AI - provide personalized upskilling, training, and corresponding certifications to technical and non-technical talent and ensure every knowledge worker has basic AI skills.

There has also been good discussion about the buy vs. build models. It is more complicated in AI because of the role of foundation models, the techniques of using those using prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning. AI is also bringing flexible consumption-based pricing options.



Overall, IMPACT24 has been an excellent and timely event, given the peak interest in GenAI and its applications for businesses to improve productivity and create value. Thanks to TechTalk Summit and IDC, we could learn more about how companies from different industries implement GenAI use cases. The event's message was loud and clear: "Start harnessing the power of Generative AI at scale, responsibly and effectively, now."

Please Contact Us to learn how you can transform and deliver immediate value cost-effectively at lower risk using Enterprise AI as a Service applications powered by Decision Intelligence from Cirucitry.ai.  

You can also read our previous blog posts on related topics:  

Harnessing Decisions Intelligence to Optimize Business Outcomes 

Enterprise AI as a Service: Going Beyond SaaS to Enable Intelligent Autonomous Businesses

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