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Investment Thesis
While being a tech laggard for much of the last decade, International Business Machines (NYSE:IBM) is now starting to see stronger, more consistent revenue growth on its way to becoming a leader in AI implementation and consulting. The tech company's Q2 results exceeded expectations by reporting strength across their core businesses-software, consulting, and infrastructure-further strengthened by the accelerated adoption of AI by enterprises. With revenue rising 4% year-over-year and a 24% increase in free cash flow, I think Big Blue's financial health is more than strong enough to help push the company into the AI sector.
IBM is well on their way to capitalize on the accelerating AI implementation wave, particularly with their watsonx AI platform and the Granite family of models. IBM's foundation models, designed with enterprise-grade security and transparency, address many of the key concerns of data privacy & control, which have prevented wider AI adoption in large organizations before. Enterprises can now implement AI solutions with a level of control and security I believe was previously unattainable in the past 12 to 18 months.
IBM's unique intersection of consulting, software solutions, and AI development enables them to offer services that cater to the scaling needs of enterprises embarking on transformative AI projects. Their unique combination of offerings allows companies to work with IBM as their partner in AI adoption while ensuring they are compliant with stringent data security rules. In my opinion, it's a really great combination.
With IBM's improving financial performance, long-term, disciplined initiatives in AI, and the ever-increasing demand for AI-driven enterprise solutions, I retain a strong buy rating on IBM. The company has the right consulting expertise and the core AI technologies they need that can drive sustained growth as AI adoption continues to accelerate.
Why I'm Doing Follow-Up Coverage
Since my last coverage update on IBM where I focused on their integration of the Llama 3 model into their AI portfolio, the company has outperformed the broader market with their stock price rising by over 19%. I believe this outperformance has been due to the market recognizing IBM's huge investments in AI and open-source initiatives, which have begun to pay dividends, particularly with the integration of Meta's Llama 3 into watsonx. IBM recognizes that picking a foundation model that's the long-run winner is a 'fool's errand' as they say. It's better to be model agnostic. That's what they are doing.
In their recent earnings, IBM accelerated (slightly) but is gaining real traction by exceeding expectations with a revenue of $15.8 billion, up by 4% year-over-year through demand for hybrid cloud and AI solutions. This performance was particularly strong in the Software segment, where revenue grew to $6.74 billion, supported by the strong adoption of hybrid cloud platforms and AI-driven consulting solutions that spilled over into software revenue. Unlike some AI companies, AI is helping IBM improve margins and growth, not shrink them. I think this is key.
The market has responded positively to these developments, and I think this is just the beginning of a potentially long-term growth trajectory.
What's unique here is that I think IBM's strong consulting expertise in software development has allowed the tech firm to work with their clients beyond mere technology in-a-box sales, it's been more of a hands-on relationship. I think this is translating to higher margins. Their strong offering allows Big Blue to integrate consulting with advanced software solutions to customize AI projects to the needs of enterprises. I think this is a key advantage. Everyone wants their AI to be custom. IBM is doing just that.
IBM Consulting, as an example, integrates AI services with a library of role-based AI assistants for enterprise customization. IBM claims this has helped consultants deliver consistent, proprietary AI tools that are scalable and are tailored to the specific demands of each client.
I think that IBM is now even more geared towards capitalizing on the AI wave. The integration of open-source AI models like Meta's Llama 3 into their watsonx, in particular, has multiplied their AI capabilities. I'm doing this follow-up coverage, so I can show how their AI vision is accelerating and what this means for the stock.
IBM's Enterprise AI Strategy
I want to start with consulting services because any business that wishes to build a sustainable product in a niche market should consider starting as a consultant so they can get paid to deliver on work for a prospective client and learn what repeatable software that client may want. In this case, consulting connects IBM's AI innovations to real-world business applications.
Through this, IBM is able to create a feedback loop where client needs and industry trends inform IBM's ongoing AI innovations to create better software they can license. IBM can quickly adapt their AI software solutions to be nimble in what is an insanely competitive market.
CEO Arvind Krishna touches on this during the Q2 earnings call:
...our consulting services are critical in helping clients build their AI strategies from the ground-up. We also continue to see our infrastructure segment play a larger role as clients leverage their hardware investments in their AI strategies.
Our book of business related to generative AI now stands at greater than $2 billion inception-to-date. The mix is roughly one quarter software and three quarters consulting signings. We believe these strong results highlight our momentum and traction with clients. Our early leadership positions us for long-term success and this transformational technology, which is still in the initial stages of adoption.
Krishna added that the open-source nature of their technology has allowed IBM to expand that market into the millions of developers who run Linux on their own machines or their corporate machines. He added that they can "experiment, add their innovation and either give it back to the community or actually reserve it for their enterprise."
...Open sourcing our models under the Apache license gives our clients the freedom that what they add onto our underlying open model, they can keep to themselves.
Now, to the developer point, putting all of that machinery into Red Hat Linux now gives us an avenue to open it up to developers as they can go experiment and play. By the way, I will turn around and tell you that for a developer who's not running production, who's just playing with things like all people do it. On a MacBook, you can begin to play around with models that are in the low tens of billions of parameters. That's a massive market that opens up.
They get the freedom and flexibility that they don't have to give it back to us unless they want to. I am not actually concerned about this gives away the IP, as we have found through whether it's Red Hat Linux or whether other people have found through Mongo or other people have found through Hadoop, enterprises do look for and the last few days have certainly shown us, people look for patching, people look for security, people look for backward compatibility.
It's Paying Off
With Q2 revenue at $15.77 billion, IBM beat analyst expectations of $15.62 billion. The company has been struggling for a while to perfect a turnaround. This might just be the kicker.
The company also reported adjusted earnings per share of $2.43, which beat the expected $2.17 per share. This was partly powered by improvements in gross margins, which increased to 56.8% from 54.9% in the prior year.
The company raised their full-year free cash flow expectations to over $12 billion alongside this. I think they are now starting to hit their stride.
Most enterprises now prefer AI solutions that are deeply integrated into their existing workflows, which IBM caters to through their custom software development, integration, and eventual software licensing services.
On this note, the launch of Meta's Llama 3.1 model, particularly the 405 billion parameter variant, follows IBM's partnership with the social media giant from a year ago. Meta (META), for their part, works to develop high-quality, large-scale foundation models, while IBM manages the tailoring, modifying, and implementing of these models. Llama 3.1, in particular, offers organizations an open-source model that rivals some of the best proprietary options available but has the advantage of customization and control. I think this is big.
Valuation
Don't get me wrong, IBM is definitely not the fastest growing company, but management appears to be strong capital allocators, shown by their impressive return on equity (ROE) of 36.36%, significantly outpacing the sector median of 4.61% by a wide margin (688.12%). Combined with solid profitability margins, including a gross profit margin of 56.09% and an EBITDA margin of 23.45%, the tech giant operates well above industry averages of 49.54% and 10.15%, respectively.
Despite these strong fundamentals, IBM trades at a forward price-to-earnings (P/E) ratio below the sector median. The company's forward non-GAAP P/E ratio stands at 19.58, compared to the sector median of 23.58-a discount of -16.97%. I think this undervaluation is due to IBM's lackluster growth over the past decade, where annual revenue has dropped significantly from its peak in 2011/2012.
I believe IBM's valuation should now match the sector median P/E given their accelerating growth with AI. If we saw shares coverage on the sector median P/E, this would represent a potential upside of approximately 20.42% in the stock, not including dividends.
Risks
Non-deterministic models, or the tendency of LLMs to produce different outcomes even when presented with the same input, means many current bleeding-edge AI models may be unpredictable and inconsistent in their results. I think for IBM, the models being non-deterministic could limit the adoption of these key AI models in critical enterprise applications, such as in finance or healthcare, where precision is paramount above everything else.
To offset this, IBM's partnership with Meta positions them, I believe, in a position to leverage AI with their customers (and use bleeding-edge AI) through Llama 3.1. Given that AI technology is not yet fully deterministic, IBM uses Meta's model as a foundation to address immediate needs while setting the stage for more significant, exponential benefits as the technology matures.
By integrating Llama 3.1 into their watsonx platform, IBM can help enterprises start realizing tangible improvements in areas such as automation, customer engagement, and operational efficiency while leaving the sensitive AI integrations for later when machine learning specialists can learn how to make these models deterministic.
Bottom Line
I think IBM is on the cusp of even stronger growth due to their discipline, but nimble position in the AI ecosystem. Despite this, their price-to-earnings ratio still reflects a company that has been slow to innovate and grow. Now with a strong financial foundation and an aggressive push into AI, IBM has transformed and is positioned to capitalize on the trend.
Big Blue's opportunities in front of them, particularly in AI and cloud services, are immense. The enterprise AI landscape is expanding, and IBM is uniquely positioned to lead this transformation. Given this, I retain a strong buy rating on IBM. I am confident in their capability to capitalize on the accelerating AI wave.
