Is Your AI Operation Achieving Long-Term, Sustainable Growth?

We are all witnesses to the reimagining of an industry cycle. AI is reshaping how to create value and how to build a competitive advantage. However, many organizations are engaged in today’s transformational period with short-term thinking.

Many are tackling individual AI tasks while overlooking their long-term sustainability consequences. This narrow approach speaks to a reality that was discovered in our recent global report, The AI Acceleration Gap: Why Some Enterprises Are Surging Ahead.

According to the report, AI investments have expanded 250% — from $2.5 million to $8.7 million per organization. However, only 13% of the 1,400 IT decision-makers we surveyed are seeing measurable returns. This is in direct contrast to the 64% who said they’ve achieved substantial benefits from AI. This group of AI Leaders are three times more likely to successfully scale deployments.

What’s causing this disparity? For starters, AI Leaders are tackling AI investments like a diversified financial portfolio. This includes balancing financial returns with operational resilience and ethical responsibility. They believe this approach gives them a competitive advantage, an opportunity to achieve long-term growth and the ability to avoid the accumulation of unsustainable technical debt.

Sustainable portfolio thinking is critical today

In our AI-driven world, entire industries are being reimagined. The traditional move-fast-and-break-things approach to building is no longer viable. It’s likely the organizations that dominate the next decade will be those that use portfolio thinking to build operationally resilient, economically viable and ethically sound AI within a disciplined framework.

Portfolio thinking widens your field of view. Instead of focusing narrowly on individual wins, it helps you confront the broader questions that shape sustainable AI, such as:

• Operational capabilities: What should we create to sustain our AI systems over the long term?
• AI investments: How can we create compounding economic value in the face of escalating costs?
• Stakeholder trust: How can we ensure our AI investments strengthen trust?

Amazon offers a clear example of how a portfolio-driven strategy creates sustainable transformation. At the start of the internet era, the company developed complementary capabilities across multiple dimensions rather than pursue disconnected e-commerce tasks.

Three layers in a sustainable investment framework

How can your organization evolve from an isolated AI approach to a disciplined strategy? At Rackspace, we’ve seen that sustainable portfolios apply investments across three layers to reinforce operational, economic and ethical sustainability — the foundation layer, the growth layer and the innovation layer.

Foundation layer: building a sustainable bedrock (50% to 60% allocation)

A strong AI portfolio has a set of rule-based, deterministic applications. The goal is to achieve economic value within six to 12 months while building infrastructure and achieving ethical transparency. This helps establish the governance framework, data pipelines and organizational ability to help enable sustainable scaling.

Foundation investments should employ specific integrated sustainability filters, including:

• Economic: Demonstrate ROI within 18 months
• Operational: Employ existing skills while building AI capabilities
• Ethical: Strengthen stakeholder trust with transparent decision logic

Growth layer: building a sustainable competitive advantage (30% to 40% allocation)

Growth layer investments are advanced agentic AI applications that operate with autonomy. They make decisions within defined parameters to create operational excellence, economic value, and ethical governance capabilities.

A good example of creating economic efficiency while achieving operational scale and maintaining ethical customer service standards is Bank of America’s virtual assistant. It has facilitated over three billion customer interactions, with more than 98% of users finding the information they were looking for.

Growth investments require advanced sustainability integration, including:

• Restricted access: for operational security
• Fail-safe defaults: to protect performance and trust
• Logging: to capture operational health, economic impact and ethical decision making

Innovation layer: securing a sustainable future advantage (10% to 15% allocation)

Innovation investments are strategic bets on fully autonomous agentic AI systems. They are designed to create a competitive advantage that is both transformational and sustainable. The investments have the potential for achieving a long-term competitive advantage. However, they may require capital and sophisticated multidimensional risk management.

A good example is DHL's Resilience360 platform. It utilizes AI-powered analytics and machine learning to help over 13,000 users worldwide predict and mitigate disruptions in their supply chains.

Portfolio maturity to drive strategic allocation

When applying the portfolio approach to AI strategy, decision makers should adjust their portfolio allocation according to their sustainability maturity, for example:

• Sustainability beginners (70% foundation, 25% growth, 5% innovation): Build integrated operational, economic and ethical capabilities via high-impact applications while also establishing governance frameworks.
• Sustainability adopters (50% foundation, 40% growth, 10% innovation):  After launching controlled experiments with autonomous systems, leverage established infrastructure to deploy sophisticated applications.
• Sustainability leaders (40% foundation, 45% growth, 15% innovation): Balance market leadership with operational excellence via autonomous systems. This is where the AI Leaders in our study operate. They have achieved the Holy Grail: running projects more sustainably and more strategically.

This level can help companies sidestep normal pitfalls, such as over-investing in sophisticated applications before prioritizing short-term economic gains over operational resilience, establishing sustainable foundations or deploying AI without considering long-term ethical implications.

The sustainable, competitive imperative

How large is the opportunity for establishing sustainable AI portfolios? It’s shrinking every day. But businesses that develop sustainability-driven AI strategies have the potential to lead the pack in their marketplace.

We predict that the future will be led by AI leaders who understand that we are deploying new technologies while rebuilding entire industries on sustainable foundations. By balancing operational resilience, economic returns and ethical responsibility, leaders who embrace the integrated approach will be well positioned to define the AI revolution and AI’s long-term sustainability.

Download the Rackspace report, The AI Acceleration Gap: Why Some Enterprises Are Surging Ahead.