RESEARCH REPORT
Technology Vision 2025
AI: A Declaration of Autonomy—Is trust the limit of AI’s limitless possibilities?
10-MINUTE READ
January 7, 2025
In brief
- Leaders must prepare today for an imminent world in which AI is everywhere and acting autonomously on behalf of people.
- New autonomy for AI also means new autonomy for systems and people, and a refined relationship with trust.
- Opportunities will be lost unless business leaders secure enough trust from employees and consumers to engage with AI's unprecedented capabilities.
4 Emerging Trends of AI, autonomy and trust:
Our technology trends explore what happens when AI acts autonomously at the center of enterprise technology, speaks on behalf of your brand, inhabits robotic bodies and collaborates on behalf of employees.
01
The Binary Big Bang: When AI expands exponentially, systems are upended
As gen AI becomes central to enterprise tech, development costs plummet, new systems abound, and digital agents gain autonomy—transforming applications as we know them.
Organizations are entering a generation-defining moment of transition: the Binary Big Bang. When foundation models cracked the natural language barrier, they kickstarted a shift in our technology systems: how we design them, use them, and how they operate. They are pushing the limits of software and programming, multiplying companies’ digital output, and vastly accelerating innovation. We are now at the precipice of more abundance, abstraction, and autonomy in our technology systems than ever before, and the decisions enterprises make today will profoundly impact what they can achieve for the next decade.
Forward-thinking enterprises are already leveraging this transitional period to secure their future growth. The key is to look beyond immediate AI applications and grasp the deeper shift happening in the broader technology foundation. Take agents—they're not just augmenting software but fundamentally altering its nature. We're seeing AI features that allow users to interact with complex software through natural language alone, and coding co-pilots that are transforming developer efficiency.
As we navigate this transition, three pillars of tomorrow's technology are starting to emerge: abundance, abstraction, and autonomy. Abundance is driving down the cost and time of digital system creation. Abstraction is democratizing technology, expanding who can use it and how. Autonomy promises a future of frictionless, intent-based systems, but also demands a radical new approach to system development and training.
The ongoing transformation in technology is upending conventional norms. It’s evolving some apps from toolboxes of features that users can access into platforms with agents that can use tools and features on people’s behalf. As these capabilities advance, it begs the question: do apps, the way they’re designed today, still make sense, or will end users go directly to agents in the future? The Binary Big Bang is rendering many of our fundamental assumptions about digital technology obsolete, offering a unique opportunity to reshape and revolutionize business competition.
Today’s technologies are not the endgame—they are how we are getting there. A technology future of abundance, abstraction, and autonomy is what leaders need to be planning for.
48%
of executives say AI agents would improve flexibility of their organization’s digital architecture, while 43% cited enhanced innovation.
77%
of executives agree AI agents will reinvent how their organization builds digital systems.
78%
of executives agree that digital ecosystems will need to be built for AI agents as much as for humans over the next 3-5 years.
How do you preserve trust?
To harness the power of autonomous systems responsibly, companies must implement robust monitoring and strategic training. This involves tracking systems' data access, direction, and output quality, while establishing clear governance and communication plans to build employee trust. Additionally, training these systems to make sound decisions through explainable processes, such as grounding agents with code and functions, is crucial. Businesses currently using agents should define feedback loops that reinforce desired outcomes, while those taking a slower approach should proactively map out these interactions to align future training with business objectives.
Next steps
If you’re an early adopter?
- Define your new digital ecosystem
- Identify the highest value opportunities of tomorrow’s technology landscape
If you’re just preparing to start?
- Map out ecosystem partners’ agentic AI offerings
- Start experimenting with agents internally
If you want to take a slower approach?
- Prepare your digital core for agents
- Watch signals to predict upcoming industry impacts
02
Your Face, in the Future: Differentiating when every interface looks the same
AI Agents can personalize customer interactions at scale, but brands must protect their unique voice to avoid becoming generic.
As businesses integrate gen AI into customer interactions, a key question emerges: What is your AI’s personality? Where generic agents could lead to a bland experience, diluting brand identity, personified AI offers a solution, breathing personality into agents and unlocking customer relationships like we’ve never seen before.
The challenge is making digital representatives stand out as the customer experience becomes more autonomous. By increasingly using third-party chat platforms and agents, often designed to be generic-sounding, businesses risk losing the uniqueness of their brand voice. But this is not a call to turn away from autonomy or AI in customer experience. It’s a call to use personified AI to marry AI’s scale and efficiency with the humanizing power of a company’s brand and values.
Envision a future where every customer interaction is guided by a familiar face—a personified chatbot that embodies a beloved mascot or an influencer’s persona. This agent operates on the company's channels or can join conversations on other AI platforms. Over time, it gets to know customers individually, building trust by taking relevant actions and leveraging digital tools to meet their needs exactly on their terms. A chatbot like this isn’t just personalizing interactions at the surface level—it’s building trusted relationships, autonomously, and managing thousands of these conversations at once.
But while the building blocks of this vision—AI agents, frameworks to give agents relevant data access, and the growing field of personified AI—exists, enterprises still need to connect the dots with intention. It is time to bring gen AI to customer-facing roles with purpose. Done poorly, businesses could see the magic of their brands eclipsed. Done right, it's the beginning of a new era in customer relationships and trust.
Companies that successfully introduce AI with personalities are looking at a technology that can build relationships with customers and meet their needs at an unprecedented scale. They’re taking personified brand, and personified AI, and they’re inventing the personified business.
80%
of executives agree that chatbots that all sound the same are creating differentiation challenges for organizations like theirs.
77%
of executives agree their organizations will need to proactively build trust between personified AI and their customers.
95%
of executives report establishing or maintaining a consistent personality will be important or very important to their customer-facing AI agents over the next 3 years.
How do you preserve trust?
To preserve trust, it is essential to keep your chatbots aligned with your brand by meticulously reviewing and continuously monitoring their training data, working with AI experts to set clear rules and boundaries that limit their knowledge and vocabulary. Additionally, demonstrate restraint in data collection by respecting user privacy, preparing for regulatory challenges, and providing transparent, customizable privacy settings. This approach ensures that your AI interactions are beneficial, respectful, and aligned with your brand, ultimately building a trustworthy, personified brand that users can rely on.
Next steps
If you’re an early adopter?
- Infuse personality into your gen AI efforts
- Ensure guardrails around your autonomous systems
If you’re just preparing to start?
- Develop a personification rollout strategy for high-impact customer experiences
- Build relationships in the growing personified AI ecosystem
If you want to take a slower approach?
- Audit chatbots across your organization
- Start the conversation between your technologists and brand
03
When LLMs Get Their Bodies: How foundation models reinvent robotics
Robots with embedded LLMs have generalist versatility, enabling them to take on new tasks in human spaces beyond today’s highly-programmed use cases.
A watershed moment is underway in robotics as foundation models transform robots from linearly-programmed and single-purpose to versatile machines that can reason. LLMs, VLMs, and Robotics Foundation Models are giving robots ever greater autonomy in the physical world—allowing them to better understand physics and their environment, have spatial awareness, interact with people, and understand complex instructions and take safe and accurate actions in response. This transition will require the creation of a full built for purpose stack but will grow the use cases and operability of robotics while simultaneously making them more flexible, re-purposeable, and enduring.
Imagine asking a robot to bring you an item and having the robot understand your request, identify the relevant object, and provide it—all without task-specific programming. This is now possible, as foundation models unlock a new chapter in robotics and many of the limits that once kept robots relegated to factories and warehouses away from the general population start to fall away.
What’s more, the rise of generalist robotics software, adaptable to various tasks and environments, is driving new interest in multipurpose robot hardware. Even as the hardware components inside robots become increasingly purpose-built, the bodies they’re composed into are evolving to be increasingly general-purpose. Designs like humanoids are expected to drive ever greater robot integration into our world, revolutionizing industries and allowing businesses across nearly every industry to rethink physical operations and workflows.
Now is the time to start building your robotic future. As robots with generalist brains and bodies learn to navigate new environments, connect with people in them, and “think” through problems autonomously, their reach and impact will vastly and rapidly expand. Robots are about to go places they have never gone before, and it’s up to you to reimagine your business for this new world.
What’s happening is machine intelligence is moving into the physical world, and robots are starting to demonstrate reason and autonomy.
74%
of executives agree their organization sees the promise of adaptable and intelligent robots.
80%
of executives believe natural language communication will increase trust and collaboration between humans and robots.
75%
of executives agree that organizations will need to factor in the dimensions of responsible AI principles as robots get deployed into physical settings.
How do you preserve trust?
It's natural to feel apprehensive about robots, especially when they're entrusted with critical tasks like security. To build trust, be transparent about their decision-making processes, programming, and accountability. Position robots as co-pilots, enhancing employees' experiences rather than replacing them. Highlight their exceptional communication skills and implement a feedback system to continuously improve their collaboration with your team. By prioritizing safety, ethics, and openness, you'll be well-equipped to navigate the complexities of responsible AI and foster a harmonious blend of human and machine capabilities.
Next steps
If you’re an early adopter?
- Chart your path to scale
- Push experimentation to new areas
If you’re just preparing to start?
- Partner with robotics leaders
- Lean into co-innovation opportunities
If you want to take a slower approach?
- Track the robotics landscape
- Run a robotics ideation sprint
04
The New Learning Loop: How people and AI are defining a virtuous cycle of learning, leading, and creating
When gen AI is diffused through an organization, every employee has the full power of their organization behind them, which expands the autonomy of both people and AI over time.
Across industries, leaders are racing to capture the immense advantages of AI, agents, and the autonomous systems they power—and naturally one of the first applications that comes to mind is automation. But while the future of work will undoubtedly be molded by gen AI, and employees certainly recognize its value, worries and distrust around how that happens risk holding back the technology’s adoption and potential today.
The solution lies in gen AI's accessibility. It's rapidly becoming ubiquitous, enabling leaders to enhance jobs and ignite innovation from the ground up. Unlike traditional top-down automation, gen AI can foster a dynamic interplay between workers and AI. By pivoting from mere automation to fostering autonomy, and equipping employees to steer their own AI initiatives, leaders can transform every employee into an innovator.
This approach not only unlocks new skills and boosts engagement, but also fuels unprecedented innovation. Picture a marketer harnessing data science to validate a new idea they’ve had, or a truck driver designing and prototyping an app to make their inventory process smoother—the possibilities are boundless when employees are given the autonomy to innovate with AI.
By distributing AI and empowering employees with autonomy, businesses can achieve exponential innovation and growth. It's about trusting people to lead the transformation, encouraging them to become automators and explore new ideas independently. Far beyond optimizing workflows, this approach liberates human potential with AI and fosters a culture where every employee is part of the engine for innovation and growth.
In the past, various technologies were pushed top down, and while there might have been delays to their full diffusion, enterprises were largely in the driver’s seat. This time, people need to be the engine of that evolution—a challenge with the specter of automation looming over it.
68%
of executives report a need to upskill/reskill their employees, including those with disabilities, in gen AI tools and technologies, within the next 3 years.
95%
of executives expect the tasks their employees perform will moderately or significantly shift to innovation over the next 3 years given the influx of automation enabled by gen AI.
75%
of executives believe that only by building trust with employees will organizations be able to fully capture the benefits of automation enabled by gen AI.
How do you preserve trust?
To swiftly harness the power of gen AI, prioritizing employee buy-in is essential. Engage your workforce in planning, clearly communicate your innovation goals and long-term vision, and address concerns about job automation. Additionally, redefine and formalize career growth pathways, setting clear expectations and providing educational opportunities to build AI competency. This approach will not only alleviate fears but also empower employees to drive the transformation and excel in a future shaped by AI.
Next steps
If you’re an early adopter?
- Develop a platform to manage workforce changes
- Start an AI Bounty Program
If you’re just preparing to start?
- Get specific with your automation strategy
- Understand what keeps workers engaged
If you want to take a slower approach?
- Align on AI policy
- Monitor industry trends