The Accenture Technology Vision Report 2024 is centered around the narrative that AI will unleash the next level of human potential as new emerging technologies will become more human. In fact, 95% of executives agree that making technology more human will massively expand the opportunities of every industry. The report begins with examples of high-impact technologies, noting that generative AI has the potential to impact much more than just the task at hand. It’s also starting to profoundly reshape organizations and markets.
More human technology means more ethical questions, and many of these questions require answers before we can proceed. Accenture notes that 93% of executives agree that with rapid technological advancements, it is more important than ever for organizations to innovate with purpose.
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Accenture begins by stating that the relationship between humans and technology is at an inflection point, and that it’s time to make technology human by design. The main takeaway is this: When technology is more human, it’s more accessible.
“Human by design is not just a description of features,” according to Accenture. “It’s a mandate for what comes next. As enterprises look to reinvent their digital core, human technology will become central to the success of their efforts. Every business is beginning to see the potential emerging technologies have to reinvent the pillars of their digital efforts. Digital experiences, data and analytics, products, all stand to change as technologies like generative AI, spatial computing, and others mature and scale.”
The Technology Vision Report 2024 identifies four key trends that make us human: the way we think, act, feel, and understand one another.
A Match Made in AI: Reshaping our relationship with knowledge – People are asking generative AI chatbots for information – transforming the business of search today, and the futures of software and data-driven enterprises tomorrow. Accenture explores how technology is starting to imitate the way we process information. These are not just superficial changes to the way we interact with technology; they are rooted in memory structures designed and organized similarly to people’s brains. The earliest changes are starting in search and will come to disrupt the way we approach knowledge and knowledge management. Here are some predictions about “A match made in AI”:
- By 2025, a leading airline will announce that customers are just as satisfied with chatbot agents as human agents.
- By 2027, data poisoning (adding malicious data to ML models) will be a top cybersecurity threat to enterprises.
- By 2028, major corporations will have proprietary chatbots to assist with knowledge management, research, and task completion.
- By 2029, AI advisors will receive more search traffic than traditional search engines.
- By 2031, a smartphone will launch that replaces the app-based interface with an agent-based one.
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Meet My Agent: Ecosystems for AI – AI is taking action, and soon whole ecosystems of AI agents could command major aspects of business. Appropriate human guidance and oversight is critical. In Meet My Agent, Accenture is tracking the evolution from AI that can perform singular tasks to AI agents that, with appropriate oversight, can work with one another and act as proxies for people and enterprises alike. Today we might think of it as automated assistants for individual interactions, but tomorrow the agent ecosystem has the potential to underpin the entire business-to-business landscape.
- By 2025, a new code repository will launch for open-source code written by agents.
- By 2026, three-fourths of knowledge workers will use copilots every day.
- By 2028, the first truly lights-out car manufacturing plant will open.
- By 2030, one-half of home mortgages will be approved and serviced by agents.
- By 2032, authorities will dismantle an insider trading ring that was using intelligent agents to collect protected information.
The Space We Need: Creating value in new realities – The spatial computing technology landscape is rapidly growing, but to successfully capitalize on this new medium, enterprises will need to find its killer apps. In The Space We Need, Accenture is watching the emergence of a new spatial computing medium, and the applications taking advantage of its capabilities to pierce the physical-digital divide. The metaverse struggled under the weight of ever-expanding definitions and expectations, but the value in the technology behind it has never been in doubt.
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Our Bodies Electronic: A new human interface – A suite of technologies – from eye-tracking to machine learning to BCI – are starting to understand people more deeply, and in more human-centric ways. Our Bodies Electronic looks at an emerging suite of technology that is starting to sidestep the unnatural technology interactions of the past to read and understand people more closely than has ever been possible.
In this article, we will take a deeper look into the first two trends, A Match Made in AI and Meet My Agent.
A Match Made in AI: Reshaping our relationship with knowledge
Our relationship with data is changing – and with it, how we think, work, and interact with technology. The entire basis of the digital enterprise is getting disrupted. A big realization in the report is this: “We’re so used to it that most people don’t even realize how much search has permeated their lives.”
Another big takeaway in the report is the importance of data. Data is one of the most important factors shaping today’s digital businesses. Companies have the chance today to reimagine how information works throughout their organization, and in doing so, invent the next generation of data-driven business. And now with generative AI, a digital butler is finally in the cards, according to Accenture.
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The way we interact with data, and how we live, work, and think, is all changing. Enterprises need to be just as pliable – or a new generation of data-driven businesses will rise without them. Data silos do exist and are harmful. According to a recent Gartner survey, “47% of digital workers struggle to find information or data needed to effectively perform their jobs.” This is where generative AI can help. The report notes that 95% of executives believe generative AI will compel their organization to modernize its technology architecture.
A super insightful part of the Accenture report was the exploration of Large language models (LLM) as a new data interface. Accenture. Imagine if instead of a search bar, employees could ask questions in natural language and get clear answers – across every website and app in the enterprise. With an accessible and contextual data foundation, enterprises can start to build this – and there are a few different options to explore. Here are four LLM options:
- First, companies can train their own LLM from scratch, though this approach is rare given the significant resources required. Some of the leaders here are AI powerhouses, including Amazon, OpenAI, Google, Meta, AI21, and Anthropic.
- A second option is to fine-tune an existing LLM. Essentially, this means taking a more general LLM and adapting it to a domain by further training it on a set of domain-specific documents. OpenAI’s GPT-3.5, for instance, can be fine-tuned using a business’s own data, to hone it into a more custom or efficient model for certain tasks.
- A slight variation on this is also gaining traction. Enterprises are beginning to fine-tune smaller language models (SLMs) for specialized use cases.
- Lastly, one of the most popular approaches to building an LLM advisor has been to ground pre-trained LLMs by providing them with more relevant, use case-specific information, typically through retrieval augmented generation (RAG). As suggested by the name, this combines an information retrieval system with a generative model, which can be either self-trained or used out-of-the-box and accessed through an API. Grounding an LLM through in-context learning and RAG takes much less time and compute power, and requires far less expertise than training LLMs from scratch or fine-tuning. Salesforce’s Einstein GPT uses this approach to ground generative AI chatbot responses too, when connected to one of OpenAI’s LLMs or any other external LLM.
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Accenture also notes that the data going into the LLM – whether through training or the prompt – should be high-quality data. That means it should be fresh, well-labeled, and unbiased. Training data should be zero-party and proactively shared by customers, or first-party and collected directly by the company. Beyond accuracy, the outputs of the generative AI chatbot should also be explainable and align with the brand.
Accenture concludes by advising that generative AI chatbots should be subject to continuous testing and human oversight. Companies should invest in ethical AI and develop minimum standards to adhere to. And they should gather regular feedback and provide training for employees as well.
Accenture conclusion: Generative AI is a game-changer for data and software. Just as search did decades ago, LLMs are changing our relationship with information, and everything from how enterprises reach customers to how they empower employees and partners stands to transform. Leading companies are already diving in, imagining and building the next generation of data-driven business. And before long, it won’t just be leaders – it’ll be the new way digital business works.
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Meet My Agent: Ecosystems of AI
Can an AI agent launch your next product? According to Accenture, 96% of executives agree that leveraging AI agent ecosystems will be a significant opportunity for their organizations in the next three years. Accenture shares real use cases of AI adoption in businesses to launch new products and services. Today, for example, AI can detect manufacturing flaws, but agents could enable true lights-out manufacturing. AI is already processing orders, yet agents could sell your product and then get it to the customer’s door. Just as the moving assembly line allowed Ford to reimagine what the automobile market could be, agent ecosystems will let companies reinvent what they offer and how they offer it.
AI assistants are maturing into proxies that can act on our behalf. As these agents emerge, the resulting business opportunities will depend on three core capabilities: access to real-time data and services; reasoning through complex chains of thought; and the creation of tools – not for human use, but for the use of the agents themselves. Along with humans to guide and oversee them, these advancements will allow agent ecosystems to complete tasks in both the physical and digital worlds, Accenture’s report includes several AI breakthroughs in 2023 and industries that are leading the AI agent adoption revolution. The report notes that as assistants or copilots, agents could dramatically multiply the output of individual employees. For the enterprise processes that will always depend on humans, agents will act as collaborators.
Businesses will need to think about the human and technological approaches they need to support these agents. From the technology side, a major consideration will be how these entities identify themselves. Today, machines make up 43% of identities on enterprise networks. The most profound statement in the report regarding a machine and human future of work is this:
“In the era of agent ecosystems, your most valuable employees will be those best equipped to set the guidelines for agents.”
The key success factor is your company’s core values and guiding principles. Trust must be your company’s #1 core value. (That’s my opinion). The report reminds us that a company’s level of trust in its autonomous agents will determine the value its agents can create. Your human talent is responsible for building that trust. This means as agents get access to the right information, humans must also teach agents how to reason about that information. A powerful statement from the report:
“Agents are only as valuable as the humans who teach them.”
How can companies start on this agent co-creation journey? Companies can start by weaving the connective fabric between agents’ predecessors, LLMs, and their support systems. By fine-tuning LLMs on your company’s information, you are giving foundation models a head start at developing expertise. This is not a technology-led journey, but rather a cultural one. Accenture reminds us that every action your agents take will need to be traced back to your core values and mission, so it is never too early to operationalize your values from the top to the bottom of your organization.
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Meet My Agent conclusion: “Agent ecosystems have the potential to multiply enterprise productivity and innovation to a level that humans can hardly comprehend. But they will only be as valuable as the humans that guide them; human knowledge and reasoning will give one network of agents the edge over another. Today, artificial intelligence is a tool. In the future, AI agents will operate our companies. It is our job to make sure they don’t run amok. Given the pace of AI evolution, the time to start onboarding your agents is now.”
To learn more about Accenture’s Technology Vision 2024 Report – Human by Design: How AI unleashes the next level of human potential – you can visit here.
