In 2023, enterprises experimented with AI to streamline operations, reduce costs, minimize errors, assist customers, and automate repetitive tasks. With the ongoing generative AI boom, the possibilities for using AI within large organizations are expanding. As we look forward to 2024, let’s explore the hottest artificial intelligence trends shaping the enterprise landscape.
Summary of trends.
- AI systems become more flexible.
- Self-improving AI systems emerge.
- Interest in AI ethics continues to skyrocket.
- Demand for AI-related skills rises across sectors.
- Companies that embrace AI continue to thrive.
- Policymaker interest in AI surges.
- Hyperautomation: The future of streamlined enterprise operations
- Responsible AI gets prioritized.
- The AI arms race heats up: cybersecurity vs. cybercrooks.
- NLP revolutionizes AI's impact on the enterprise
[ Learn what the experts have to say about the future of AI in 2024. Get the 2024 AI Outlook. ]
1. AI systems are becoming more flexible.
Traditional AI models typically specialize in processing a specific type of user prompt, whether image- or text-based. However, a paradigm shift is underway with the emergence of a new generation of AI models known as "multimodal" systems. Unlike their predecessors, these advanced models can process a diverse range of inputs seamlessly. They can adeptly handle various media types, such as text, images, audio, video, and even code.
These flexible AI systems go beyond the limitations of single-domain processing, enabling them to navigate and excel in multiple domains simultaneously. This opens doors to a wide array of applications previously considered beyond the reach of artificial intelligence. The adaptability of these models makes them well-suited for addressing complex enterprise challenges and expanding AI's impact across companies and industries.
2. Self-improving AI systems are emerging.
AI systems now actively contribute to their own enhancement. Nvidia, a trailblazer of this paradigm shift, uses AI reinforcement learning agents to optimize AI autonomously. This self-improvement technology enables dynamic analysis, pattern recognition, and continuous optimization, propelling AI technology beyond traditional programming constraints. The result is AI that evolves and improves over time, promising accelerated advancements in performance and adaptability. This innovative approach departs from static programming, ushering in an era where AI becomes an autonomous learner, poised to excel in a mixed-autonomy landscape with human oversight.
3. Interest in AI ethics is continuing to skyrocket.
The rapid evolution of generative AI underscores the urgent need for increased attention to ethical considerations. While advances in Gen AI and other tech tools hold enormous potential for social good, they also expose enterprises to severe ethical risks. To align with corporate purpose and societal values, business leaders should prioritize cross-disciplinary collaboration internally and externally to establish ethical standards that contribute to the public good and generate value for their organizations, foster consumer trust, and attract future talent.
4. Demand for AI-related skills is rising across sectors.
The demand for AI-related skills is on the rise across US industries. Recent reports indicate a significant surge in global job postings related to AI and generative AI, with a more than twofold increase observed from July 2021 to July 2023. Specifically, the employer hiring platform Indeed has witnessed a remarkable uptick of nearly 4,000% in searches for generative AI positions in the past year, complemented by a 306% rise in corresponding job postings during the same timeframe. As the market sees a proliferation of AI products, the need for AI talent intensifies in enterprises operating in healthcare, financial services, and other data-centric industries.
[ Watch the video: Start delivering end-to-end process automation to integrate humans, systems, RPA, and AI. ]
5. Companies that embrace AI are continuing to thrive.
McKinsey's research delivers a clear message to businesses: Embrace AI sooner rather than later.
According to the findings, companies initiating AI adoption now and evolving their strategies over the next five to seven years could experience a remarkable 122% surge in free cash flow by 2030.
In contrast, organizations that neglect implementing an AI strategy might face a decline of up to 23% in their free cash flow during the same period.
Early adopters of AI are experiencing immediate benefits, and the widespread proliferation of generative AI will significantly impact the global economy, potentially contributing over $4 trillion annually. This contribution will complement the existing $11 trillion generated by the integration of AI and automation. Consequently, capitalizing on AI trends remains paramount for any large organization seeking to sustain its competitive edge.
6. Policymaker interest in AI is surging.
Governments and policymakers worldwide are focusing on AI more than ever before. An analysis by the 2023 AI Index Report reveals significant growth in the number of bills related to "artificial intelligence" passed into law. Understanding the implications of this trend will be essential for enterprises in 2024 and beyond. The surge in legislative activity signals a shift in how governments approach AI governance. Enterprises must anticipate potential changes in regulations, compliance requirements, and industry standards associated with advances in AI technologies.
7. Hyperautomation is bringing AI, machine learning, automation, and data together.
Hyperautomation means combining automation technologies like AI, machine learning, and robotic process automation to make enterprises more agile, efficient, and adaptable. According to Gartner, by 2024, 65% of large organizations worldwide will have deployed some form of hyperautomation.
The strategic integration of AI into front- and back-office operations is essential for maximizing employee productivity and driving meaningful improvements in decision-making processes. AI-driven customer interactions and the implementation of AI-enhanced process automation in the back-office contribute significantly to operational excellence. However, achieving this level of integration using traditional developer tools can be resource-intensive and demands a deep understanding of complex business processes.
That’s where process modeling comes into play. It involves graphically mapping out a workflow in a clear and intuitive diagram known as a process model. While a process model is essentially a visual representation of a workflow, utilizing a low-code platform enhances its effectiveness. Leading low-code platforms offer user-friendly process modeling capabilities, allowing swift transformation of process models into applications without the need for coding skills.
Here's what a business process model looks like in Appian:
Businesses everywhere are struggling with inefficiency and just can’t seem to digitize workflows fast enough. Process mining tools employ AI to pinpoint areas where processes are experiencing delays or bottlenecks, along with identifying the root causes of these impediments. Beyond boosting process efficiency, the application of AI in product innovation holds immense potential for creating game-changing offerings, enabling businesses to develop more sophisticated, tailored products that resonate with evolving consumer demands.
Yet, leveraging this transformative technology necessitates a harmonious blend of technical expertise, creative thinking, and deep market insights.
Companies too cautious about keeping pace with AI-powered automation trends risk becoming irrelevant. And the consequences extend beyond immediate operational effectiveness, impacting long-term strategic viability.
For enterprises today, engaging with AI and hyperautomation is not merely an enhancement opportunity but a fundamental requirement for survival and success.
The ability to navigate and harness the power of AI-driven technologies is now a defining factor in determining an enterprise's resilience in the face of relentless technological change.
[ Explore more on AI and process automation. Get the Gartner® Emerging Tech Impact Radar: Hyperautomation. ]
8. Responsible AI is being prioritized.
The transformative benefits of AI technology are accompanied by inherent risks, making it imperative for enterprises to embrace the principles of responsible AI. The concept is rapidly gaining traction as a critical facet of AI governance, encompassing attention to ethical, moral, and legal values throughout a technology's development and deployment. In 2024, global AI regulations will increase, necessitating a responsible approach to compliance to ensure competitiveness and mitigate potential liabilities.
The rapid evolution of technologies like gen AI and other emerging AI innovations will intensify the pressure to proactively create robust governance frameworks, institute review boards, and engage in challenging discussions and decision-making processes to navigate the complexities of responsible AI effectively.
9. The AI arms race is heating up: cybersecurity vs. cybercrooks.
The convergence of artificial intelligence and cybersecurity will be a trend to watch as organizations increasingly rely on AI to safeguard their digital assets and defend against fast-evolving cyber threats. AI-powered cybersecurity is not just a trend but a necessity in an increasingly digital and interconnected world. Enterprises must leverage AI technologies to stay ahead of cyber threats, protect sensitive data, and maintain the trust of customers and stakeholders. This fusion of AI and cybersecurity will shape the security landscape now and in the future.
Enhanced threat detection and response: AI-driven cybersecurity systems will become even more adept at identifying and mitigating cyber threats in real-time. Machine learning algorithms will continuously analyze vast datasets to detect anomalies, patterns, and potential security breaches faster and more accurately than traditional methods.
Predictive analysis: AI-powered cybersecurity will move beyond reactive measures and focus on predictive analysis. Organizations can proactively strengthen their security posture and reduce the risk of cyberattacks by identifying potential vulnerabilities and threats before they materialize.
Automated incident response: AI-driven cybersecurity tools will automate incident response procedures, enabling organizations to respond to security incidents rapidly and effectively. Automatic incident response can significantly reduce the dwell time of threats within a network, minimizing potential damage.
Security orchestration and automation: AI will facilitate the orchestration and automation of security tasks and responses, allowing security teams to focus on more complex threats. In contrast, routine tasks are handled efficiently by AI systems.
Cloud security: As more businesses adopt cloud-based infrastructure, AI will be crucial in securing cloud environments. AI-driven tools will continuously monitor cloud resources and detect unauthorized access or data breaches.
[ Want to succeed at AI? Get specific about your use cases. Learn how by watching the Appian World presentation: 6 Ways AI Makes a Difference to Your Business. ]
10. NLP is revolutionizing AI's impact on the enterprise.
As generative AI gains traction, natural language processing (NLP) emerges as a driving force reshaping AI capabilities. NLP enables machines to better understand and interact with human language, and it's a vital component of everything from document automation to chatbots and conversational AI. In 2024, NLP's popularity will continue to soar as it empowers AI across industries. Here's how NLP will impact AI in the coming year:
Enhanced conversational AI: NLP's evolution will usher in more sophisticated chatbots and virtual assistants with significantly improved ability to understand and respond to human speech, leading to better customer support and user experiences across sectors.
Data insights unleashed: Market leaders will harness NLP's advanced capabilities to extract valuable insights from text data sources. AI analytics will rely on NLP to decipher complex text data, enabling more informed decision-making.
Hyper-personalization: Businesses will leverage NLP-driven AI to deliver hyper-personalized customer service. AI systems will provide more accurate and relevant recommendations and content by understanding user preferences and sentiments.
Healthcare revolution: NLP's impact will extend to healthcare, transforming diagnosis, data management, and patient care. It will facilitate a better understanding of medical records and improve healthcare outcomes.
Cross-industry integration: NLP's versatility will foster cross-industry integration, giving rise to domain-specific solutions and innovations. AI-NLP integration will drive innovation across industries from finance to retail and beyond. NLP's growing popularity and capabilities reflect its crucial role in advancing AI technology. As businesses increasingly recognize its potential, NLP will continue to shape the AI landscape, making interactions between humans and machines more seamless and insightful.
- Advanced document extraction: Human-AI collaboration requires human verification even when AI handles manual tasks. Appian AI Skills will soon offer enhanced document extraction, enabling users to train a custom model for accurate data extraction from unlabeled fields using a small set of example documents.
- Self-service analytics for business users: Unlocking organizational information is crucial for informed decision-making in the age of AI. Appian's data fabric empowers developers to discover, unify, secure, and optimize enterprise data. In version 23.4, Appian enhances the data fabric for business users with self-service analytics. Users can access a secure data catalog, generating reports with aggregation, filtering, sorting, and formatting without additional development or data configuration. The addition of AI Copilot integrates generative AI and large language models for faster and more accessible analysis.
Watch the Product Announcement Webinar for a full recap of what’s new in Appian 23.4.
Key takeaways.
In the rapidly evolving landscape of artificial intelligence trends, enterprises stand at the crossroads of transformative opportunity and critical challenge. The trends shaping the AI narrative in 2024 are not mere forecasts but indicate a paradigm shift in how large organizations operate and innovate.
AI’s foundational pillars—large language models (LLMs), machine learning (ML), and natural language processing (NLP)—are reshaping industries and businesses through technologies like voice and facial recognition.
AI systems are breaking traditional constraints, becoming more resilient, and propelling technological progress.
The demand for AI-related skills is skyrocketing, contributing to faster tech innovation.
Early AI adoption promises immense financial potential for organizations, and hyperautomation is becoming essential for enterprise efficiency.
The surge in attention to AI ethics calls for a responsible approach to AI implementation. Governments are focused on AI governance, and the fusion of AI with cybersecurity is becoming critical.
Natural language processing (NLP) is revolutionizing human-machine interactions and shaping the future of AI.
C-Suite impact: What do the 2024 AI trends mean for CXOs?
As enterprise CXOs navigate the AI frontier in 2024, embracing these trends becomes imperative for sustained growth, innovation, and competitive advantage. Those who strategically integrate AI into their operations, prioritize ethics, adapt to evolving regulatory landscapes, and foster a culture of continual learning will thrive and unlock unprecedented innovation, efficiency, and growth.
[ For enterprise leaders: Fuel your organization’s productivity with AI. Discover the next-generation AI-powered platform for process automation. Watch the webinar. ]
