Build Your AI Blueprint: Takeaways from The December 2023 AI Summit New York

calendar iconFebruary 23, 2024

As artificial intelligence (AI) makes its way further into every corner of our lives and aspect of our workplaces, it continues to present a myriad of challenges and opportunities. Businesses that are strategic and intentional about AI will be the ones to benefit and outpace the competition. However, there is no “how to” guide—not yet, at least.

To plan for the still-emerging potential of AI, business leaders must understand the landscape and stay ahead of the technology as it continues to develop. In mid-December, The 2023 AI Summit New York was host to fast-growing AI startups, industry experts and leaders of Fortune 500 companies alike. It was a forum to trade stories, share successes (and failures), and discuss new frontiers of AI. This article explores the top five trends and developments in AI, revealing a “blueprint” on how to harness its power and create true competitive advantage.

The Top Five Trends in AI

1. Specialized vs. Generalized AI

AI is currently defined as either specialized or generalized. Specialized AI excels in discrete tasks like virtual assistants, customer chatbots, or document verification, which is a significant leap in automation capabilities in and of itself. In contrast, generalized AI—replicating human behavior across diverse activities—is still a dream. That’s okay because today’s business leaders are not thinking about AI that can do it all yet. Rather, they are focused on very specific objectives and tailoring their AI models to accomplish them. Think of Netflix’s recommendation engine, which uses AI to personalize content recommendations and has grown to account for 80% of viewer activity.

2. Proof of Concept Value

The shift from proof of concept to the demonstration of tangible value is accelerating. Businesses are emphasizing real and measurable value creation with a direct link to top- and/or bottom-line impact. Here, effective storytelling is critical and extends beyond the technical intricacies of AI and to the benefits derived from implementation, with a clear connection to the business strategy. Consider Agilent Technologies, which has used AI in its Waldbronn, Germany, manufacturing site to achieve a 35% increase in quality (less waste/rework), a 44% increase in productivity (improved labor economics), and a 48% increase in output (greater scale efficiencies).

3. The AI Task Force

Successful AI deployment needs robust governance. According to a recent IBM survey of over 2,500 business leaders, the average ROI for AI projects is less than 6%, compared to more than two times for best-in-class companies. Standing up an AI Task Force plays a pivotal role in setting the right guardrails for decision-making on use cases, resource allocation and risk mitigation. Consider Mastercard’s AI Governance Council, comprised of cross-department senior leadership, which works to oversee end-to-end AI activities across the enterprise and ensure alignment with its values and business objectives. Effective AI governance spans the full AI lifecycle, from data architecture and data security to technology development and implementation to change management and training.

4. Synthetic Data

Synthetic data has emerged as a game-changer and is proving to help address challenges with data scarcity and sensitivity. Crafted to mirror real-world samples, synthetic data allows for training AI models without compromising data privacy and regulatory guardrails. Across industries, companies like Roche (clinical data), American Express (transaction data), and Transformco (customer data) are already leveraging synthetic data to approximate real-world data and create more “at-bats” for training AI models. The benefits of synthetic data are still emerging and show significant promise in creating new methods for training and enhancing AI.

5. The Human-AI Link

The future of work depends on seamless collaboration between humans and AI. As organizations work to design mechanisms for responsible deployment and ethical AI oversight, thinking simultaneously about human-AI interaction is also critical. Consider AlphaFold, an AI developed to predict 3D protein structure. This step-change for silico drug discovery is only realized when also considering the crucial role of human scientists in the R&D process—study design, data preparation and validation, and interpretation. From UX design and training programs to methods and tools for communication, consideration of these elements is critical for a future where humans and AI work side-by-side.

The Top Five Developments in AI

1. Democratization

AI’s reach now extends beyond data scientists and is empowering more employees across more functions. From code reviews to copywriting to medical billing, the perception of AI as a threat to job security is giving way to that of a catalyst for innovation and unlocking new levels of possibilities at all levels across the organization. At the summit, we heard from Opé Majek, a fashion stylist who was able to use AI tools like Midjourney to transform from stylist to designer, and not only win at Maison Meta’s inaugural AI Fashion Week, but also take her designs to market on Revolve.

2. Building Trust in AI

As AI becomes more integral to business operations, building trust and comfort in its applications are crucial. According to a recent survey by PWC, one in three employees have negative feelings about AI. Additionally, concerns with accuracy, bias, reliability, intellectual property, etc., are real and necessitate thoughtful and intentional development. Standing up cross-functional and user-driven teams to engage actively during development, testing, and implementation can help to ensure the smooth integration of AI into everyday work processes.

3. Multimodal AI

Google’s Gemini multimodal AI model marks a pivotal development in the AI landscape. Multimodal AI can seamlessly integrate text, image, video and audio, unlocking a myriad of new possibilities. From AI-driven patient consultations to adaptive curriculum educational platforms to sign language translation, these models are an incredible leap in the potential of AI.

4. The Dark Dock

Industries like transportation and logistics, to name a few, are undergoing a radical transformation with the combination of AI and robotics. The idea of the “Dark Dock” is reshaping workflows by enabling continuous 24/7 operations. By using AI and robotics to handle repetitive tasks and increase up-time, companies can redirect resources and focus on higher-value, strategic activities. Consider FedEx, which is working on AI to fully automate operations both in (always-on) and between (self-driving on long-haul routes) its distribution hubs. The Dark Dock exemplifies the transformative impact of AI to rethink long-held ways of working.

5. “Data + AI” as Currency

Competitive advantage is shifting from access to vast, proprietary datasets to the strategic integration of data with AI. Access to the data alone is no longer enough, and the real value is now in deploying sophisticated AI models to extract new, deeper, and different types of insights from that data. “Data + AI” is quickly becoming a necessary ingredient for achieving sustainable differentiation.

Five AI Blueprint Steps

As organizations work to define their AI journey, a strategic and intentional approach is imperative. The following steps provide a practical guide to navigating the AI journey effectively:

  1. Establish a governing body (GUIDE): Set up an AI Task Force to define critical guardrails and establish responsible AI practices.
  2. Align on opportunity areas (FOCUS): Focus efforts on a few defined opportunity areas to direct resources and maximize impact.
  3. Pick the play (VALUE): Explore opportunities for AI across supplementing everyday tasks, reshaping critical functions, or inventing new revenue streams, creating alignment with the organization’s strategy and business objectives.
  4. Build trust (TRUST): Identify a champion, build a coalition, and anticipate the people impact to get ahead of change management.
  5. Accelerate learning (LEARN): Drive adoption and create new ways of working through focused and ongoing learning programs, making improvements along the way.

Your Guide Forward

Embracing AI needs a mindset that blends innovation with adaptability. These five steps serve as an outline to help craft and set an AI strategy up for success.

Our Strategic Growth & Innovation team is comprised of strategists and consultants who help organizations see market trends, like AI, before the competition to anticipate the needs of customers and take advantage of new untapped growth opportunities. If you need assistance establishing strategic AI alignment within your organization, reach out to us today.

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