In September 2024, Marc Benioff, CEO of Salesforce, declared a “hard pivot” toward autonomous AI agents, envisioning a seismic shift in business operations. This bold move gave birth to Agentforce, an AI-driven platform designed to revolutionize customer service, sales, and marketing. Benioff articulated the vision behind Agentforce:

“Agentforce represents the Third Wave of AI — advancing beyond copilots to a new era of highly accurate, low-hallucination intelligent agents that actively drive customer success. Our vision is bold: to empower one billion agents with Agentforce by the end of 2025. This is what AI is meant to be.”

This strategic move signals a broader industry transformation — the aggressive integration of Generative AI (GenAI) into core business processes. Organizations worldwide are racing to deploy GenAI, but is this a breakthrough strategy, an overhyped trend, or something else entirely?

Regardless of perspective, one thing is certain: the global sprint toward GenAI exposes significant gaps in organizational readiness, execution, and strategic application for most certainly GenAI, arguably the most disruptive technology to date, at least in this century. However, this lack-of-readiness issue is true for all emerging technologies.

Emerging Technology — No Longer Optional

Years ago, emerging technology was approached with extreme caution and usually a tactical focus. Organizations would test maturing technology in narrow applications, deploying incrementally to maintain stability and avoid operational disruption. Highly refined performance optimized operations and their associated processes were the holy grail. Today, that measured approach is obsolete.

Advancements in business methodologies, globalization of competition, and the acceleration of both product delivery and internal infrastructure tooling demand much more from us tasked with ensuring operational performance. We focus on optimizing enterprise performance toward ever shifting strategic objectives. Operations and their associated processes not only have to operate at optimal performance but must be ever ready for rapid adaption. Operations must be lightweight, high performing, and utterly adaptable. Optimizing cycles run in weeks and perhaps months, not months and years. This optimization effort is heavily reliant on technology — platforms managed on dispersed data centers and networks, enterprise processes rendered into software workflow that may reach billions of individuals wherever they might be, and continuously performance enriched by emerging technologies.

Modern business environments demand immediate technological adaptation that supports strategic intent. Consider the landscape:

• Global enterprises operate at unprecedented complexity and scale yet must align to a unified purpose.
• Competition is relentless, emerging from every sector, every geography in a world in which an nimble David can easily fell a lumbering Goliath.
• Enterprise platforms drive optimized workflows and integrated decision-making.
• Massive datasets fuel AI-driven insights, managed in cloud-based infrastructures.

Technology is no longer just an enabler; it is the battlefield where competitive advantage is won or lost. Organizations must assess emerging technologies in real-time, extract value, and deploy strategically — or risk irrelevance. This battlefield demands that we must plan for disruption and invest in efforts that support us in thriving in disruption.

Nowhere is this urgency more apparent than in the explosive rise of GenAI.

Lessons Learned from the Hard Reality of Scaling GenAI

Integrating emerging technologies must take lessons from scaling Gen AI. Led by tools like ChatGPT, GenAI arrived like a shockwave. The technology, once seen as a distant strategic possibility, became an immediate necessity overnight. Yet, as companies rush to integrate it, they are discovering massive hurdles:

Barriers to GenAI Success:

• Scaling Challenges — A Deloitte survey found that over two-thirds of organizations report only 30% or fewer of their GenAI projects will scale within six months.
• Data Quality Issues — AI effectiveness depends on clean, structured, relevant data — something many enterprises lack.
• Regulatory & Compliance Hurdles — Uncertainty around AI governance slows adoption.
• High Implementation Costs — The cost of AI infrastructure, from GPUs to maintenance, is staggering.
• Talent Shortage — The workforce lacks AI expertise, slowing enterprise-wide adoption.
• Rapid Technological Evolution — AI models evolve so quickly that investments risk rapid obsolescence.
• Energy Consumption & Sustainability — AI workloads demand enormous energy resources, raising financial and environmental concerns.
• Market Pressures — Investors demand real ROI from AI initiatives within the next year, putting organizations under immense pressure.

While GenAI is the poster child of emerging tech, it is far from the only game-changing technology that enterprises must evaluate. It is also far from the only emerging technology that deserves our attention.

Beyond GenAI — The Emerging Technology Playbook

To truly optimize for competitive advantage, leaders must assess multiple high-impact technologies, as they support the strategy, business model, and operational demands:

Key Emerging Technologies & Enterprise Applications

• Artificial Intelligence (AI/GenAI) — Powers automation, predictive analytics, and personalized customer experiences.
• Internet of Things (IoT) — Enables real-time monitoring, automation, and predictive maintenance.
• Blockchain — Enhances security, transparency, and traceability in transactions and operations.
• Robotic Process Automation (RPA) — Reduces costs by automating repetitive, rule-based tasks.
• Cloud Computing — Scales IT infrastructure, enhances collaboration, and reduces costs.
• Big Data & Analytics — Unlocks real-time insights for better decision-making.
• 5G & Edge Computing — Reduces latency, enabling real-time processing and smart automation.
• Cybersecurity & Zero Trust — Protects critical data, infrastructure, and digital identities.
• Web3 (W3) — Decentralized internet using blockchain for user ownership, privacy, and interoperability.

A more detailed assessment of emerging technologies, their applications, benefits and challenges can be found in the tables at the bottom of this article.

Most of these technologies are not completely new per se, but their capabilities and potential impacts, positive and negative, are rapidly evolving. When combined, they amplify their individual benefits, unlocking radical improvements in decision-making, efficiency, and risk mitigation. All emerging technologies have versions of the GenAI challenges — market pressure for ROI turnaround, performance optimization and scaling, data quality, compliance, internal deployment and operating expertise, resource consumption, and implementation, upgrade and maintenance costs, and finally obsolescence. These potentially critical technologies beg for developing an organizational capacity to assess emerging technology opportunities for use in supporting organizational strategy.

Applying Emerging Technologies — Finding the Fit

Before diving into cutting-edge tech, organizations need to understand the technology’s best uses. We must first ask:

• What business problem are we solving?
• How does emerging technology support our goals?
• What are our operational constraints?
• What ROI can we expect?
• What are the risks, including obsolescence and compliance?
• What resources are required for implementation and scaling?

Strategic alignment must come before technology adoption, ensuring that investments drive tangible performance gains rather than chasing hype.

The Emerging Technology Pipeline: A Continuous Optimization Approach

Given optimization and emerging technology is a forever game, we don’t address emerging technology as a project. Rather we need to build an assessment and integration capability that operates similarly to a product development effort. It requires expertise, a structured approach, and fingers on the pulse of the evolving technology that might solve your business needs. In other words, it requires an upfront and continuous investment.

Expertise — Whether we train our internal experts on emerging technology or contract an expert, we need to staff for understanding the applicable emerging technologies for their potential use, limitations, and complications. Finding or developing this sort of expertise is likely the greatest challenge to and longest lead effort for our emerging technology evaluation effort. By their nature emerging technologies have few experts associated with them.

Applications — Not only do we need to develop a deep understanding of the technologies, we need to evaluate their applications. We need to understand our strategic objectives, the performance requirements those objectives demand, and how the emerging technologies might support them at what cost. We need to answer all of the above fit questions to ensure we are making sound technology integration investments.