If tech providers were more clear with buyers about what they actually do, it would help reduce AI confusion! Tough love from Hackett Group CEO Ted Fernandez

If the technology providers actually described their capabilities a little bit more precisely, I think it will help all of us as well.

A cutting observation from Ted Fernandez, CEO of digital transformation consultancy The Hackett Group, and one that will surely resonate with many as the AI hype cycle continues to rage unabated and nonsense like the supposed ‘SaaSpocalypse’ reduces Wall Street short-termists to running around like Chicken Little expecting the software sky  to cave in on their heads.

In its marketing pitch, Hackett Group promises “gen AI expertise with unmatched digital world class performance insights to re-define excellence”.  The firm works with a number of partners, including Oracle, SAP and ServiceNow.

Late last month the firm published its 2026 Enterprise Key Issues Study, which found that organizations are “moving beyond incremental AI deployment to re-imagine their operating models and driving significant gains across customer and employee experience, risk management and compliance, and business productivity”.

Among the key stats in the report:

• More than half of respondents  (54%) are scaling AI adoption to enhance customer satisfaction and experiences, with three-quarters (76%) reporting improvements of 25% or more in key metrics.
• Half of respondents are scaling AI adoption to improve risk management and compliance outcomes, with 57% claiming a 25% or greater improvement in Employee Experience.
• 69% are looking to AI to improve employee productivity, with 80% of those citing 25% or greater gains.

The ability to evolve operating models will be critical as organizations look beyond gen AI to an agentic pathway. The report notes:

Organizations that act with urgency to re-imagine work and the workforce with AI will begin to realize their agentic potential: cost savings and positive improvements in productivity, quality, and customer and employee experiences.

Futures

Despite its own gen AI specialism, Hackett is looking towards its own agentic destination, according to CEO Ted Fernandez:

Our strategy has been to develop highly differentiated gen AI-enabled capability that leverages our unique expertise as well as our proprietary IP. The goal was to be able to accelerate and, more importantly, enhance the value of solutions we deliver to clients. Our AI leadership and relevance is being defined by our distinct capabilities to help clients identify, evaluate, design and deploy high-impact AI solutions utilizing our AI XPLR platform. We are not surprised by the changes required by the AI transition. We were early adopters and anticipated the required changes.

But not everyone has, he adds, and in some respects AI has complicated buying decisions:

Although demand for digital transformation remains solid in traditional areas, it continues to be impacted by thoughtful decision-making as organizations assess competing priorities partly due to economic concerns and also partly due to the consideration and also confusion of emerging gen AI technologies and what they offer.

We have not been surprised by the powerful potential to the compute and inference power of the Large Language Models (LLMs) to drive transformative change, but rather the confusion created by the frequent introductions of new technology, primarily build capabilities, is where we believe the confusion lies. 

What requires greater understanding is what is necessary to realize high returns from the deployment of the available emerging capabilities, he argues:

To assess and design high ROI solutions requires client-specific process knowledge in order to reimagine and enhance the new workflows to determine Agentic workflows, which should be designed and deployed, which can provide targeted returns.

This is where Hackett comes in, he suggests, noting that turning to LLM providers alone isn’t necessarily helpful:

The rapidly emerging build capabilities which are being introduced by the client providers, like Anthropic and OpenAI, are only accelerating and reducing the cost to build agents and agentic workflows. However, they do not eliminate the need to fully understand the exact client-specific business process requirements, the client's existing automation footprint, and the need to assess existing and potential data sources necessary to fully optimize the value of AI in the design, build and deployment of solution. This is without even considering what it takes to fully then execute a high-impact, high productivity solution, which impacts both the number of people that support that activity as well as the new cognitive capabilities that are going to be utilized and how.

As to the wretched  ‘SaaSpocalypse’ fearmongering, Fernandez argues that the transition to AI and increased automation is disruptive to the traditional software and services market. But he adds:

What has not been equally or properly reported is the Total Addressable Market increase for enterprise automation that will be delivered when and as existing automation footprints extend into the cognitive and agentic workflows and therefore, who will provide it. Increasing automation opportunity should more than offset any disruption that software and services provider experience if they expand their current application footprint and related services capability to capture the significant growth.

All organizations will need to understand the potential productivity and intelligence force multiplier that will emerge when existing static rule-based automation starts to transition to cognitive automation. We expect IT budgets to increase with increasing attention and allocations to the rapidly emerging gen AI solutions and the related opportunities and threats that it brings.

And that brings us back to his opening comment: 

Eliminating confusion will be key to accelerating the adoption. The unlimited potential of gen AI will define an entirely new level of AI world-class performance standards, driving all software and services providers to extend the value of their existing offerings with the introduction of agentic AI capability. 

My take

The Hackett Group just turned in some decent quarterly numbers with Q4 revenues of $74.8   and net income standing at $5.6 million. For the full year, revenue was $300.8 million and net income was $12.9 million.

In terms of third party vendor-related business, the firm is seeing ongoing activity coming from a number of key user footprints, including the Celonis customer base. Fernandez says:

We also continue to believe that we can bring significant value to all organizations that utilize Celonis' software and other process mining software. Our ability to ingest their valuable volume and process execution detail into AI XPLR allows us to accelerate and better inform our ideation and solutioning recommendations, which allows customers to accelerate their transformation initiatives.

But Q4 revenue from its Oracle Solutions business was down 20% year-on-year to $14 million, while its SAP Solutions counterpart reported an increase of 32% for the same period to hit $22 million in revenue. Demand for SAP services was cited as likely to be strong throughout this year, while a new AIXelerator offering which supports delivery of Oracle implementation engagements should assists revenue improvement there.  Fernandez says:

The SAP performance has been coming on for a few quarters because SAP has done a terrific job with convincing clients to migrate to S/4HANA, so that's [reflected] in our business. The Oracle sequential decline is important for us. We continue to be very hopeful that...with the AIXelerator capability rolling out inside of that practice, that it gives our Oracle group an opportunity to resume growth in 2026.

Coming up this month is a go-to-market pilot initiative with ServiceNow, a development that Hackett has been pursuing for some time, admits Fernandez:

We were trying to do something with them for months and they were looking for specific go-to-market areas to use, again, this unique capability we have and to see what the impact is in introducing their existing platform capabilities. So it's a pilot to target. We've recommended and we've discussed a specific industry that, again, the hope is to be able to launch that before the end of the month.

Onwards!