Enterprise AI solutions: IBM’s strategy for ROI and innovation – SiliconANGLE

As technological innovation frequently outpaces practical application, IBM Corp. has taken a deliberate approach to advancing cloud and enterprise AI solutions, prioritizing functionality, security and sustainable growth. The company’s AI-first strategy reflects its commitment to embedding AI across every facet of the business — not as a standalone product, but as a core driver of enterprise value.

“The companies that will outperform in the next decade will truly be AI first,” according to Arvind Krishna, chairman and chief executive officer at IBM. “This is an enormous catalyst that would drive [value] — and we can see that happening now.”

IBM’s vision for the future stretches beyond current AI capabilities to pioneering fields, such as generative and quantum computing, reinforcing its dedication to enterprise AI solutions that can drive significant innovation across sectors. Generative AI allows IBM to create systems capable of producing new forms of data — such as text and images — that mimic human creativity. This leap forward could enable advancements across sectors as IBM establishes itself in this space. Quantum computing, a longer-term investment, promises to transform industries such as finance, healthcare and cybersecurity, aligning with IBM’s goal to build a versatile, adaptable computing landscape.

“The future of our company is going to be about excelling at each of these forms of computing but also bringing them together,” Khrisna said. “This goes beyond just the model; there’s actually a lot more sophistication of what’s going to be possible.”

During theCUBE on the Ground – IBM Analyst Forum event, IBM executives expanded on these themes, engaging with theCUBE, SiliconANGLE Media’s livestreaming studio, on IBM’s strategic advancements in generative AI, data management and enterprise collaboration. They highlighted the role of AI in simplifying data complexity, the importance of partnerships for digital transformation and IBM’s commitment to positioning AI as a cornerstone for future business success.

This feature is part of SiliconANGLE Media’s exploration of IBM’s AI-first strategy, highlighting its advancements in generative AI, quantum computing, multicloud solutions and ethical innovation to drive enterprise value. Be sure to catch all of theCUBE’s coverage of the IBM Analyst Forum. (* Disclosure below.)

Elevating ROI through purpose-built enterprise AI solutions

IBM’s focus on delivering enterprise AI solutions that enhance return on investment is anchored in its development of purpose-built models, according to Sriram Raghavan, vice president of IBM Research AI at IBM. With the introduction of Granite 3.0 models, IBM aims to boost enterprise efficiency by offering tailored, high-performing and cost-effective enterprise AI models. These models are designed to meet specific business needs across various use cases, showcasing the potential for AI to drive value when applied strategically across organizations.

IBM’s Sriram Raghavan talks with theCUBE about how IBM Granite 3.0 models optimize ROI in the AI sector.

“We have done some internal benchmarking of this latest generation of Granite models with carefully curated [business process outsourcing] benchmarks,” Raghavan said in a conversation with theCUBE Research’s Dave Vellante during theCUBE’s coverage of the IBM Analyst Forum. “The Granite models are doing phenomenally well because of the value we put to the data. That allows consulting to go in and offer a differentiated value proposition with the domain knowledge of running a BPO process.”

Granite 3.0 aligns with IBM’s broader AI-first approach, embedding AI into core processes to simplify workflows and improve productivity. By focusing on enterprise AI solutions that are flexible and adaptable, IBM allows enterprises to benefit from optimized parameter subsets that reduce computational costs and improve response times, especially critical in low-latency applications, according to Raghavan.

“The ROI conversation usually comes down to … what’s the most efficient and effective way that I can get to the outcome?” Raghavan said. “Now, with Granite 3.0, we started really with sort of fit-for-purpose models for some of our applications and software. They let you do everything enterprises want to do … [retrieval augmented generation], summarization, classification [and] all of the normal fundamental building blocks of most enterprise use cases today.”

IBM also integrates advanced safety features in Granite 3.0, such as Granite Guardian, which enhances enterprise AI solutions by identifying and mitigating potential risks. This functionality enables businesses to deploy AI confidently in sensitive applications while upholding high standards of accuracy and inclusivity.

“We’re also releasing what we call Granite Guardian models,” Raghavan said. “They in some respects give you sort of this cloak of protection around the main model. You have a model, you extend data and you get data out, but you always worry about what if the model has toxicity [or] has biased information. [With] Granite Guardian models, you put them in front of the model and outside the model.”

Simplifying multicloud complexity with IBM’s hybrid solutions

IBM’s multicloud strategy emphasizes workload portability and application resilience, enabling clients to move workloads flexibly while minimizing vendor lock-in, according to Bruno Aziza, group vice president of data, BI and AI at IBM. This approach enhances IBM’s ability to deliver enterprise AI solutions that meet evolving business demands through hybrid cloud infrastructure.

IBM’s Hillery Hunter talks with theCUBE about AI trends within the industry and IBM’s strategy for giving companies greater flexibility.

“Sixty-six percent of [chief information officers] are dissatisfied with the progress they’ve made with gen AI,” Aziza said in a conversation with theCUBE Research’s John Furrier during the event. “Interestingly enough, 60% … of them do not have a consistent strategy for the transformation through generative AI.”

IBM’s multicloud solutions address complexity by fostering interoperability across cloud platforms, enabling enterprises to integrate enterprise AI solutions within diverse ecosystems, according to Hillery Hunter, chief technology officer of infrastructure and general manager of innovation at IBM. By collaborating with leading cloud providers, IBM strengthens security and enhances productivity, allowing businesses to leverage multicloud environments effectively.

“Ensemble AI and combining technologies has been a core focus of us and what we’ve been doing in our program for enabling integration of AI on the mainframe systems,” Hunter told the CUBE Research’s David Linthicum in a conversation during the event. “Using a model that is small and efficient for the targeted purpose can help an enterprise get to that value stream generation … much more quickly. Providing that optionality, to combine together the best of both worlds, is a way that we’re seeing a lot of enterprises have success.”

Central to IBM’s multicloud strategy is its partnership with Amazon Web Services Inc., which aims to enhance infrastructure scalability and data security, according to Nick Otto, head of global strategic alliances at IBM. AWS brings essential scalability and data security, allowing IBM to broaden its cloud-based offerings.

“An inflection point and acceleration happened when we decided together to launch OpenShift on AWS, which is a huge step forward in terms of trust and hybrid cloud and the fact that we both believe there’s a hybrid world in the future,” Otto said during an interview with theCUBE.

Through a connected ecosystem, both companies are enabling multi-model environments to thrive as AI use cases grow more complex and hybrid solution demands rise. AWS’ collaboration with Salesforce and IBM’s Watson Orchestrate shows their shared aim to make AI tools interoperable, according to Manu Prabhakar, director and general manager of business application partnerships at AWS.

“It ties back to the development and training of the [large language models] and the gen AI models and then on top of the high-level services,” Manu Prabhakar, director and general manager of business application partnerships at AWS, told theCUBE. “I think this is where we are working very closely in that training layer with IBM, and that’s the watsonx.governance, tying it together with SageMaker.”

Driving responsible innovation through strategic partnerships

IBM’s focus on ethical AI is reflected in its collaboration with Dun & Bradstreet Holdings Inc., highlighting IBM’s commitment to enterprise AI solutions that prioritize trusted data in AI-driven decision-making, according to Isabel Gomez Vidal, chief revenue officer of Dun & Bradstreet. This partnership emphasizes IBM’s dedication to responsible innovation by aligning enterprise AI solutions with high standards of accuracy and inclusivity.

Dun & Bradstreet’s Isabel Gomez talks with theCUBE about how companies can leverage AI responsibly by focusing on trusted data and strategic partnerships.

“It’s all about trusted and verifiable data and technology,” Vidal told Linthicum in a conversation during the event. “When you think about IBM, to me, what comes to mind is innovation, trust and responsibility. We both have very common values. We have both very strong brands. We’ve got a large customer base, and it’s important that you partner with institutions that are going to amplify the role that you play in society. I think IBM is one of them.”

IBM is also making strides in cybersecurity through its partnership with Palo Alto Networks Inc., according to Vellante. This collaboration combines Palo Alto’s expertise in security with IBM’s advancements in AI, creating a joint effort to tackle complex cyber threats. The partnership’s focus on generative AI for cybersecurity is particularly impactful because it enables rapid threat detection and response, helping organizations improve security outcomes without extensive manual intervention.

“I’m not going to go through the entire lifecycle of a threat, but as people know, lots of signals come in and have to be triaged,” Mohamad Ali, senior vice president and head of IBM Consulting, told Vellante in a recent Breaking Analysis interview. “Some of them are automatically eliminated; others require someone to look at them. They examine it and say, ‘Hey, this really needs to be investigated.’ To give you a sense, with these digital workers now, we’re able to reduce investigation time by 81%.”

(* Disclosure: TheCUBE is a paid media partner for the IBM Analyst Forum event. Neither IBM Corp., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Image: SiliconANGLE/Bing