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Last week IBM held its annual Think event in Orlando, FL. The venue was near “Islands of Adventure,” which I felt was an interesting backdrop as corporate IT has become just that: a bunch of islands of adventure. Between generative AI, ChatGPT, quantum computing and security, businesses are certainly due for a fair share of adventure over the next few years.
IBM positions Think as an event that looks into current and future technology and how companies can use this tech to transform their businesses. I’ve now had time to aggregate the content and develop key takeaways.
Also see: Generative AI Companies: Top 12 Leaders
Key Takeaways from IBM Think 2023
The business use of generative AI will be narrow when compared to ChatGPT
Ever since ChatGPT sprang into action, industry watchers and business leaders have wondered what impact it will have on businesses. With AI being the focal point of Think 2023, this was a big topic of conversation.
The reality is that ChatGPT is a broad tool used by consumers, and this does not apply to businesses. Consider search. Google is used by consumers for general search by billions of people every day. However, it is not the way businesses look for information. Financial services use applications like Bloomberg, whereas legal uses LexisNexis.
Search is valuable, but only in the narrow context of that industry. Similarly, generative AI and large language models have value, but it needs to be applied narrowly for the business world to realize value from them. To help companies accelerate their use of AI, IBM announced WatsonX, which includes foundation models, generative AI, a governance toolkit, and more.
On a related topic: What is Generative AI?
Hybrid cloud is the way forward for most organizations
Public or private, that has become the proverbial question regarding the enterprise use of cloud computing. The real answer is both.
During his keynote, IBM Chairman and Chief Executive Officer Arvind Krishna mentioned an IBM Institute for Business Value (IBV) study that found that over 75% of their customers plan to leverage a hybrid model. This is consistent with my research, although my data pointed to about 90% of enterprise-class companies using a mix of public and private.
One of the challenges with hybrid cloud, particularly when multiple providers are used, is creating consistency across the different clouds. This is where Red Hat OpenShift can add value as it creates a logical container layer making data and workloads portable across clouds. With public cloud, IBM has been a distant number four to the “big three,” but the shift to hybrid should act as a catalyst for IBM to gain ground.
lso see: Top Cloud Companies
Security needs AI to keep up with threat actors
As long as we have had cyber security, the bad guys have had a leg up on the good guys. One of the challenges facing security pros today is that there is a massive amount of telemetry data that needs to be aggregated and analyzed. There is too much for anyone to do manually, so malware often takes months to be detected.
At the recent RSA event, IBM Security announced its new QRadar Suite, which includes EDR and XDR, SOAR, and an advanced SIEM, all powered by AI. In Think Forum, I participated in a demo where the tools were used together to identify a breach, and a recommendation was given to the SOC engineer on how to correct it. While people can’t make sense of all the data being generated today, machines can, and that’s the future of security.
On a related topic: The Future of Artificial Intelligence
AI and data can close the ESG gap
During the Day 2 keynotes, John Granger, Senior Vice President IBM Consulting, showed a data point where 95% of executives say their company has an ESG plan, but only 10% of companies have made progress against it. That is a Grand Canyon size gap.
Granger discussed that the biggest barrier to executing on ESG plans is that organizations do not know where to start because of a lack of data. What’s needed is accurate data that can be measured and managed and then acted against to gauge performance and drive accountability. He mentioned how with many consumer services, people are often shown the carbon impact of things like delivery options, but we do not have that capability in the business world.
With that being said, companies do have data across a wide range of systems. There are currently hundreds of ESG frameworks available to companies but silos of data make thing more difficult. Christina Shim, Vice President and Global Head of Product Management & Strategy for IBM Sustainability Software, she talked about how AI can ingest, interpret and automate insights from the data in these frameworks.
Also, artificial intelligence will reduce manual processing by automating the classification, extraction, and validation of thousands of invoices, documents, and other data spanning multiple businesses. Consumers are watching how their brands progress against ESG goals, and companies need to use AI and data to help close the gap.
Contact centers are low-hanging fruit for AI
Where to start with AI? I get asked that a lot by business and IT executives. I always recommend an area that currently has accurate KPIs and also where a small improvement can have a big payback. This points to the contact center.
Today, businesses compete based on customer experience, which often starts in the contact center. In the AI, Automation and Data pod inside the Think Forum, IBM had set up a demo of a contact center with Watson Assistant infused into it. It created a game where the player would act as an agent and see how many inbound inquiries it could solve without AI. It then ran the same sequence with AI turned on and enabled the AI-powered virtual agent to take care of simple tasks like password resets and account balances, allowing the agent to handle more complex ones.
At the end of the game, the results were shown so you could see the improvement. Without Watson Assistant, only 3% of requests were solved compared to 65% with Watson Assistant. Businesses looking to win quickly with AI should look to the contact center as a starting point. Here is a how-to resource for building a chatbot platform quickly and easily.
On a related topic: The AI Market: An Overview
Bottom Line: IBM Think 2023
In conclusion, IBM Think 2023 provided valuable insights into the future of technology and its impact on businesses.
First, while generative AI has its merits, ChatGPT emerges as a powerful tool for consumers, but enterprises need to apply AI in different ways.
Second, the hybrid cloud approach is gaining momentum, with organizations recognizing the value of leveraging public and private clouds. Red Hat OpenShift is crucial in achieving consistency across multiple clouds and driving IBM’s growth in the cloud market.
Third, the symbiotic relationship between AI and security is imperative to combat the ever-evolving threats businesses face. IBM Security’s QRadar Suite uses AI to transform threat detection and response.
Fourth, AI and data have the potential to bridge the ESG gap, empowering companies to measure, manage, and act on sustainability goals.
Finally, the contact center emerges as the low-hanging fruit for AI implementation, revolutionizing customer experiences and enabling significant returns on investment.
Also see: Top Cloud Companies