Resource Regions: Central and Eastern Europe

Supply chain disruptions — unpredictable supplies, product shortages, increasing material costs — continue to have a profound impact on manufacturers worldwide. In response, remanufacturing, which has long been a part of the industry, has seen a surge in popularity in recent years.

Companies are turning to remanufacturing as an alternative solution when they face challenges in procuring components or encounter skyrocketing prices. This approach not only helps address immediate supply chain issues but also fosters resilience and mitigates risks by prompting manufacturers to rethink their sourcing strategies and diversify their supply chains.

Moreover, remanufacturing is emerging as a key component of manufacturers’ sustainability strategies. Beyond its role in addressing supply chain disruptions, remanufacturing delivers significant environmental benefits. By reusing raw materials, it conserves resources and minimizes waste, contributing to a more sustainable use of resources.

Remanufacturing also promotes energy efficiency, reduces emissions, and embodies the principles of the circular economy, bolstering its appeal as a sustainable practice in manufacturing. As companies increasingly prioritize sustainability goals, remanufacturing is poised to play a crucial role in achieving these desired outcomes while also addressing supply chain challenges.

What is Remanufacturing?

According to the Remanufacturing Industry Council, “Remanufacturing is a comprehensive and rigorous industrial process by which a previously sold, leased, used, worn, remanufactured, or non-functional product or part is returned to a like-new, same-as-when-new, or better-than-when-new condition from both a quality and performance perspective, through a controlled, reproducible, and sustainable process.”

At the center of remanufacturing lies the concept of the “core.” The core refers to the existing, used, or worn-out part that serves as the starting point for the remanufacturing process. This core component undergoes a series of steps, including tracking, identification, disassembly, cleaning, inspection, repair, and reassembly, to transform it into a product or part that meets the desired quality and performance standards.

Effective core management is essential for manufacturers engaged in remanufacturing. It allows them to maximize the value of core assets, manage costs, and strengthen relationships with customers and suppliers. Additionally, robust core management practices help minimize waste and environmental impact by promoting the reuse of existing materials and reducing demand for new resources.

Closing the Gap: The Need for Remanufacturing Software

Remanufacturers in discrete manufacturing environments face distinct challenges that are not adequately addressed by traditional ERP systems. While ERPs offer essential functionalities like inventory management, testing, and quality control, remanufacturers require specialized core management features tailored to their needs, including:

• Core Tracking and Disassembly: Efficiently collect and inspect individual components or parts for wear, damage, or defects, ensuring thorough assessment and tracking throughout the remanufacturing process.
• Reconditioning, Repair, and Replacement: Address wear, damage, or defects in components through reconditioning or repair processes, or replace them with new or remanufactured parts as needed.
• Reassembly: Reassemble products according to technical specifications, ensuring that the final product matches the quality and performance of the original.
• Complex Product Configurations: Manage complex product configurations, accommodating a mix of old, new, or remanufactured components while maintaining accuracy and consistency.
• Cost Estimation and Pricing: Provide accurate cost estimation and pricing based on the type of components used, enabling transparent and competitive pricing strategies.
• Traceability and Compliance: Ensure traceability and compliance with regulatory requirements by generating reports and documentation necessary for regulatory purposes, maintaining transparency and accountability throughout the remanufacturing process.
• Integration Capabilities: Seamlessly integrate with other systems such as ERP or CRM, enabling data exchange and process synchronization across the organization.

By investing in specialized remanufacturing software, manufacturers can streamline operations, enhance productivity, and ensure compliance while effectively managing the complexities of the remanufacturing process.

Regional Approaches to Remanufacturing

Remanufacturing approaches vary across the globe, with each region displaying unique drivers and focus areas.

Primarily driven by cost savings but also influenced by federal/state regulations, the North American remanufacturing market is well developed. There is growing demand for remanufactured products across automotive, electronics, and aerospace.

In Europe, the growth of remanufacturing is closely tied to circular economy principles. With a strong emphasis on resource efficiency and waste reduction, government policies and initiatives play a significant role in driving adoption.

A key manufacturing hub, Asia holds immense potential to integrate remanufacturing practices into its industrial landscape. Technological advancements and a growing awareness of sustainability issues are driving the region toward embracing remanufacturing as part of its transition to a circular economy.

Cross-regional collaboration and knowledge-sharing initiatives are important for driving progress in remanufacturing practices globally. Leveraging insights and best practices from different regions can accelerate the adoption of remanufacturing and work toward achieving shared sustainability outcomes.

Guidance for End Users: Choosing the Right Remanufacturing Software

Selecting the right remanufacturing software is a critical decision, whether it’s an off-the-shelf (COTS) solution, customized, or a packaged solution offered by vendors. Regardless of the approach, the software should address the specific needs of remanufacturers while complementing existing systems and processes.

1. Identify Your Unique Needs: Consider your remanufacturing business’ unique requirements, including core management, inventory control, quality assurance, cost savings, and regulatory compliance.
2. Comprehensive Functionality: Look for solutions that offer a comprehensive range of functionalities, addressing core management challenges while also supporting traditional manufacturing processes.
3. Ease of Use and Scalability: Prioritize solutions that are user-friendly and scalable to accommodate your business’ growth.
4. Customization and Integration: Evaluate the software’s customization capabilities to tailor it to your specific remanufacturing workflow. Assess its integration capabilities to ensure smooth data exchange with other systems, such as ERP or CRM.
5. Vendor Success Stories: Request case studies or success stories highlighting real-world implementations and measurable improvements achieved by other remanufacturing businesses. This can offer valuable insights into the software’s effectiveness and suitability for your needs.
6. Road Map and Technological Advancements: Inquire about the vendor’s road map for future software developments and how they plan to incorporate the latest technological advancements such as automation, advanced analytics, and AI. Understanding the vendor’s commitment to innovation can help ensure that the software remains relevant and competitive in the long term.

By carefully considering these factors and collaborating closely with software vendors, end users can select remanufacturing software that not only addresses current challenges but also supports future growth and innovation in their operations.

Further reading: IDC MarketScape: Worldwide Remanufacturing Management Software 2024 Vendor Assessment

AI, which is poised to accelerate change more than any technology in history, has finally seized the CEO agenda. For those who viewed AI opportunistically, the introduction of generative AI (GenAI), along with the capabilities of large language models, is serving as a wake-up call to a new era.

According to IDC’s cross-industry Future Enterprise Resiliency and Spending Survey of January 2024, 37% of respondents globally believe GenAI will make a significant impact in the next 18 months. Nearly one-quarter said GenAI was beginning to disrupt their business, with 10% reporting it had already done so. Interestingly, these impacts are being felt most strongly by organizations in Asia/Pacific, followed closely by those Europe and the U.S.

Business competition remains fierce at the regional, national, and organizational levels. Conversations with numerous CEOs and senior managers about their approach to disruptive technologies, particularly AI and GenAI, prompted me to question whether leaders are asking themselves the right questions as they navigate this disruptive landscape.

Leaders of enterprises and medium-sized companies are adopting unique approaches. Some are enthusiastic about the potential productivity offered by innovative technologies. Others take a more cautious approach, advocating a measured strategy until the benefits of these technologies are proven on a broader scale.

This dichotomy often arises in discussions about emerging technologies like AI, cloud computing, and digital twins.

I’ve compiled a dozen key questions leaders should be asking as they guide their organizations through the dynamic — and potentially perilous — landscape of disruptive technologies:

1. Recognizing Disruptive Technology

How can I determine whether it’s just buzz or a truly disruptive technology that our company can benefit from?

It’s crucial to develop a keen ability to distinguish between industry hype and genuinely disruptive technologies. This requires staying informed about emerging trends, engaging with industry experts, and fostering a culture that encourages innovative thinking.

2. Building a Self-Learning Organization

How can I know if we have a self-learning organization whose organizational structure and processes enable us to identify, test, pilot, and objectively assess technology trends?

Organizational structures and processes must be assessed to ensure they foster a self-learning environment. This involves creating channels for identifying, testing, piloting, and objectively assessing technology trends within the company and promoting a culture of continuous learning and adaptation.

3. Balancing Short- and Long-Term Focus

How can we benefit from new technology? Will a short-term focus jeopardize our competitive advantage?

Addressing immediate needs is crucial, but the long-term impact of new technology must also be evaluated. Embracing sustainable and forward-thinking strategies can help organizations avoid a myopic focus on short-term gains and instead build a competitive advantage.

4. Data Protection and Cybersecurity

Personal productivity tools are great — but what about data protection and cybersecurity?

As organizations integrate personal productivity tools powered by AI, data protection and cybersecurity must be prioritized. Implementing robust measures to safeguard sensitive information is essential to reduce potential risks and ensure stakeholder trust.

5. Technology Ecosystem

Do we need to be part of an ecosystem of technology vendors, advisors, and service providers?

Yes, it is critical to have access to a robust and versatile ecosystem of technology vendors, advisors, and service providers to navigate the complexities of emerging technologies. A collaborative approach enhances the organization’s capacity to understand, adopt, and integrate new technologies.

6. Absorbing Innovation

How can I know if my organization has the ability to absorb another innovation? Will we need to create new dedicated positions, teams, or even departments?

Assessing the organization’s capacity to absorb new innovations is critical. Hence, it must be determined if your existing structures can accommodate technological changes or if dedicated positions, teams, or departments need to be created to facilitate a smooth integration.

7. Avoiding Pilot Purgatory

In earlier technology deployment projects, we wound up parked in “pilot purgatory.” How can I know if we have learned from these experiences?

Another stop in “pilot purgatory” is possible if organizations haven’t learned from their previous technology deployment challenges. Organizations should establish clear guidelines and action plans for transitioning from pilot phases to full-scale implementation. This is vital to realize the full potential of tools like AI.

8. Constant Change

Do our leaders need training to help them understand new paradigms and guide the organization in a world of constant change?

A continual education culture should be established to navigate the relentless change associated with emerging technologies. Such training would involve understanding new paradigms, learning how to foster adaptability, and creating a learning culture that supports leaders during times of uncertainty and rapid technological shifts.

9. Balancing Human-Machine Collaboration

Who’s taking the lead: machines or humans?

Assess the roles of machines and humans within the organization. Striking a balance between automation and human involvement ensures harmonious collaboration that leverages the strengths of both, leading to increased efficiency and innovation.

10. Regulatory Aspects

Should regulatory aspects be in our focus from the first discussions of the technology?

Prioritize regulatory considerations from the outset. Proactively addressing regulatory compliance ensures a smoother integration process and mitigates potential legal and ethical challenges.

11. Contingency Planning

If we change or terminate technology at the company level, do we need a contingency plan?

A thoroughly prepared contingency plan should be in place when changing or terminating technology at the company level. This ensures minimal disruption and facilitates a smooth transition in case unforeseen challenges arise during the implementation or adoption process.

12. Talent Management

How can I know if we have the talent to cultivate talent in the coming periods?

Focus on developing and retaining talent capable of driving technological advancement. This involves identifying, nurturing, and empowering individuals who possess the skills and mindset to lead the organization through the evolving landscape of AI and emerging technologies.

The Bottom Line

Being a leader who guides other leaders in transforming and revolutionizing industries and management domains demands a distinct set of skills and qualities, particularly the ability to pose the right questions — both to oneself and to the relevant stakeholders. Sometimes, despite our vantage point at the helm, we fail to anticipate the emergence of the next disruptive technology or product.

Some leaders might assert, “I rely on intuition, experience, and advisors to perceive what others cannot.” I advise caution. When it comes to leveraging technology adoption to gain a genuine competitive advantage, only a select few can keep pace with the relentless influx of new technologies.

It’s akin to a wild goose chase. But initiating the right discussions with yourself and your team can serve as a crucial starting point, potentially leading to the capture of flocks of opportunities!

The world of partnering has never been more complex. Vendor strategies are evolving faster than ever to keep pace with changing customer buying behaviors and partner business models.

Understanding how partner business models are evolving can help vendors build a partnering framework that is robust and flexible enough to reward partner activities while remaining customer-led.

Trend 1: Partners Are Deepening Commitment to their Strategic Vendor Partner

The breadth of a partner’s portfolio can provide an indication of the level of commitment a partner gives to each vendor relationship. Partners with multiple strategic vendor relationships are likely dividing their energy and resources between multiple vendors. Partners that work with just one, two, or three core vendors will likely give greater attention to each relationship.

This is important. While each vendor has visibility into what their partners are doing with them, they may not know how they are engaging with other vendors.

IDC’s EMEA Partner Survey 2024 showed that partners derive more than half of their total revenue from activities connected to their most strategic vendor partner. Just 6% of partners expect the share of revenue connected to their core strategic vendor to decline in the next 12 months, with 45% expecting it to remain at today’s level. Half expect it to increase.

For partners, there are specific benefits from concentrating resources on a single core vendor relationship. At the vendor level, demonstrating commitment can lead to the allocation of more resources, drive new business, launch new technologies, or to co-sell and co-creation activities that drive new customer wins.

For the partner’s business model, deep commitment to a specific vendor’s portfolio and road map can provide clarity in terms of future business development planning and skills development in the organization.

Trend 2: P2P Collaboration Accelerates Within Non-Linear Go-To-Market Motions

Partners traditionally seek to serve as a single point of contact for the end customer. The customer turns to the partner to procure, deploy, and service their IT environment.

However, changes in customer buying behavior and new routes-to-market and deployment models have led to the emergence of non-linear go-to-market motions in which multiple partners can be involved at different stages of a single customer’s journey.

Customers have choices in terms of how they procure, consume, and optimize their IT environments. They can involve a unique combination of marketplaces, platforms, and partners.

IDC’s EMEA Partner Survey 2024 shows that 60% of partner revenues are now direct payments from end customers. This means that 40% of partner revenue is coming from elsewhere — as a sub-contractor through another partner, fund disbursement from a marketplace operator, or payments from vendors.

Trend 3: Looking Beyond the Primary Activity of Partners

Many vendors used to categorize their partner base according to their primary activity. Partners that primarily focused on reselling vendor products and solutions were categorized as VARs. Partners that derived most of their revenue through services were labelled as some form of managed services or consultancy services provider.

Results of our survey suggest there are potential risks in this approach. Most partners now operate multiple partner business models that span sell, service, and build roles for the customer. While only a small number of partners in the survey self-identified as cloud service providers, for example, a significant number offer this as a secondary business model.

It is increasingly important for vendors to consider the activity mix of each individual partner to uncover how they engage with the customer. Vendors that only engage with a partner based on their primary business activity are potentially leaving opportunities on the table to drive additional customer engagement through other areas of expertise and capabilities the partner possesses.

Bottom Line

Gaining a deeper understanding of the activity mix and commitment levels of partners is key for vendors to allocate resources based on partner potential and to look for untapped opportunity within their existing partner base.

Knowing how your partners interact with other vendors and customers — and knowing how important you are to their overall business and what their long-term strategy is — has become critical to inform vendor ecosystem strategies.

To learn more, listen to IDC’s 2024 Channels and Alliances Predictions webcast, or reach out to discover how we can help unlock partner potential for vendors of all sizes.

In today’s digital landscape, where AI can churn out content in seconds, marketers face a unique challenge: How can we create narratives that stand out? Let’s explore strategies for crafting compelling and differentiated stories in the era of generative AI (GenAI).

1. Connecting the Dots

Marketers must start by connecting the dots between their promotional goals, their target audience, and a narrative that sets them apart from competitors. Relying solely on AI-generated content won’t suffice. Instead, strategic architects of brand stories must emerge.

2. The Power of Unique Market Data

Leveraging unique market data is crucial. Dive deep into analytics, trends, and IT buyer behavior. What insights can be gleaned from data that others might overlook or might not have access to? Perhaps hidden patterns or emerging needs exist that GenAI hasn’t discovered yet. Tap into this data to create narratives that resonate.

3. Insights Beyond Algorithms

GenAI analyzes vast amounts of information, but it lacks context. Unique insight comes from understanding not just what the data says but also why it matters and to whom. Ask: What motivates our audience? What pain points do they face? How can our product or service genuinely make an impact?

4. Customer Success Stories

Compelling customer success stories resonate because they’re authentic, relatable, and emotional. GenAI can help write these narratives, but marketers must discover, create, and curate them — and find the right audience.

5. The Art of Storytelling

GenAI generates content, but it can’t create captivating and unique stories. Marketers should not passively rely on GenAI. They should use it as a creative partner, stepping up to the role of the storyteller. Weave together facts, emotions, and aspirations. Whether it’s a blog post, a white paper, or an entire campaign, storytelling remains a uniquely human skill.

Conclusion

In the age of GenAI, marketers are both collaborators and curators. Collaborate with AI tools like GenAI to streamline content creation, but also curate the essence of your brand through unique narratives. By joining the dots, leveraging data, and telling authentic stories, marketers can thrive. Remember: GenAI can write — but marketers create the story.

Interested in a deeper understanding of the issues discussed here? Contact Dominique Bindels at dbindels@idc.com.

Also, you might be interested in the following complimentary IDC guides:

Increase Customer Lifetime: The B2B Growth Marketing Guide for Tech Vendors

AI: Unleashing Strategic Sales – Driving Tech Investments in 2024

B2B Marketing & Sales Guide to Outcome-Focused Conversations

The EU’s new Corporate Sustainability Reporting Directive (CSRD) has thrown a chill on the business processes of organizations: Companies must modernize their applications and data foundations to enhance their reporting capabilities.

The struggle of companies in Europe to comply with the CSRD was on display at the ChangeNOW global summit, held in Paris at the end of March. Participants at the event — which seeks to map sustainable initiatives, best practices, tools, and technologies — revealed that organizations are lagging when it comes to implementing CSRD.

This is in line with results of IDC’s recent European IT Services Survey (N = 700), which found that just 25.6% of European organizations expect to deploy tech to improve sustainability KPIs as a transformation initiative in the next two years.

The CSRD is having a huge impact on organizations: It imposes reporting standards that compel organizations to publish their ESG information, which must then be verified and audited. All industrial sectors, from large accounts to SMBs, are subject to a staggered compliance timetable: The first reports must be published between 2025 and 2026 for large accounts, and in 2027 for SMBs.

Everyone agrees on one point: It’s a race. The timetable is forcing the acceleration of activities in data collection and qualification, methodologies and best practices, to structure and industrialize the creation of these reports.

CSRD weighs heavily at all levels of organizations. It requires a review of business processes and the organizational model, and, therefore, the modernization of core business applications — where the data is. New platforms or custom developments may need to be deployed to consolidate ESG data.

After examining their data lakes and the shift toward new data architectures, many businesses perceive this as a transformational endeavor.

Like any IT project, such complexity brings opportunities for services providers to support organizations with compliance. IDC surveys have shown that 41.2% of organizations expect partners to play a key role in implementing their sustainability strategy and achieving their objectives.

The Scaling Problem of Legacy Finance

Let’s examine where CSRD creates a bottleneck. Among the processes impacted by the CSRD is that of the finance department. Today, the CFO is one of the guardians of the transformation of the finance function, whose scope has been extended to non-financial matters and CSR.

For example, the French bank Crédit Agricole and cosmetics specialist L’Oréal have entrusted the finance department with their CSRD projects. Experienced in standardized financial reporting, the CFO has the difficult task of reproducing and improving processes by integrating CSRD.

Logical, but still difficult to implement. One of the biggest challenges is getting the different personas impacted by CSRD — and the associated data — to sit at the same table to find the right communication channel and vocabulary to communicate.

These human interconnections represent a real challenge in terms of governance but are necessary to deploy an application modernization strategy and convert the new operational model and business processes into a revitalized IT structure.

Financial IT systems are often very mature. CSRD requires them to scale rapidly to support new workloads in only three years. This includes related data initiatives: the mapping of data sets, the overcoming of information silos, increasing automation, and supporting heterogeneous files (PDF or Excel, for the most part).

The legacy must be modernized within the timeframe of the CSRD. But urgency means risks must be controlled. For example, misunderstanding the regulation and the requested data could have a negative impact on technological engagements and procurement.

Using GenAI to modernize legacy applications and make them “CSRD ready” has been explored to collect, map, and consolidate data, generate appropriate information for criteria, or automate the storytelling inside the CSRD reports.

Capgemini has detailed how GenAI could accelerate gap analysis and identify which data is lacking and which data is relevant for presentation. L’Oréal discussed how it believes that GenAI is key to education and acculturation on the criteria and wording of the regulation.

This scenario is in line with our vision for application modernization strategies in Europe.

The implementation of the CSRD — and, by extension, the major theme of sustainability — represents a powerful driver for adapting processes, revitalizing part of the application estate, and establishing a coherent link between IT and new business requirements.

Revitalizing applications to optimize business processes is a key theme of IDC’s European Application Modernization Strategies research program.

Modernize with a Sustainability/ESG Integration Platform

The challenges include making the regulation a starting point for a more global strategy, and placing CSRD and sustainability at the center of the organization’s decision-making and business innovation.

We believe this requires building an enterprise architecture, including modular and loosely coupled components, to integrate systems, applications, and data in a flexible and sustainable way over time.

Such a sustainable integration platform will de-silo business applications, facilitate the continuous collection of data, the industrialization of analytical reporting, and the connection to ecosystems. In short, it means building a dynamic CSR link in the value chain and anticipating the evolution of reporting obligations.

Ransomware attacks have been one of the most high-profile scourges of business over the past decade — and the threat shows no signs of abating. If anything, it has become more prevalent as “ransomware as a service” has lowered the entry barrier for threat actors.

Innovation by cybercriminals keeps security teams on high alert. When governments and security agencies advise organizations not to pay ransom, attackers may switch to extortionware approaches.

Or, sticking with ransomware, they may use AI to augment their capabilities, refine their lures, automate attacks, or hit hundreds or thousands more organizations than they would have been able to previously.

This Is Going To Hurt

According to IDC’s Future of Enterprise Resilience Survey, conducted in November 2023, 63.4% of EMEA organizations with 500 or more employees suffered a ransomware attack that blocked access to their systems or data in 2023.

Which assets are being impacted? According to the survey respondents, the most frequently impacted resources were collaborative applications (37%) such as MS 365 or Google Workspace. These were followed by virtual or physical servers (35%) and public cloud IaaS and PaaS (also 35%). For 34% of organizations, ransomware attacks impacted their partner, supplier, or customer systems.

These impacts reflect the infrastructure and environments in which most modern organizations operate: cloud-based infrastructure and platforms running cloud-based collaborative applications on enterprise licenses for cost efficiency and productivity, often within broader digital ecosystems to enhance operational efficiency.

Targeting what has become the critical infrastructure for operational capability gives cybercriminals the greatest leverage over their victims. The hackers strive to ensure there is no choice but to pay the ransom.

The Best Defense is… Multi-Layered

Despite the rising volume of attacks, more than one-third of the surveyed organizations stated that no ransomware attacks had managed to block access to their systems or data. These organizations highlighted some of the key technologies that helped them detect the attacks before the malware was able to deploy.

The most frequently cited tool was a cloud security gateway/cloud access service broker (CASB, 30%). This aligns with the operational environments described above, placing protection where it is needed most. Deploying a CASB provides visibility and control over cloud environments and assets, enabling quicker detection and containment of potentially malicious activity.

Threats can come from within the organization as well as outside. A further 26% of respondents said they used specific security analytics aimed at detecting insider threats. The third most common response was SIEM systems (25%), which help by correlating data from multiple sources to identify suspicious patterns and anomalies before an attack. Organizations also mentioned that NDR, identity analytics/UEBA, and EDR helped with detection.

Fundamentally, there is no single technology that is a silver bullet against ransomware. Effective protection depends upon a layered approach that aligns security controls to the environment, infrastructure, and processes of the organization.

As attacks grow more prevalent, fueled by ransomware as a service and AI-augmented attack campaigns, EMEA organizations need to be on their guard with a mix of technologies to detect and contain malware payloads before they can be deployed.

San Francisco-based OpenAI’s introduction of ChatGPT on November 30, 2022, marked a significant milestone in the development of large language models (LLMs) and generative AI (GenAI) technology. The launch by OpenAI, the creator of the initial GPT series, sparked a race among technology vendors, system providers, consultants, and app builders. These entities immediately recognized the potential of ChatGPT and similar models to revolutionize industry.

2023 saw a surge in efforts to develop GenAI tools that are smarter, more powerful, and less prone to hallucinations. The competition led to an influx of innovative ideas and tools aimed at harnessing the capabilities of LLMs. The goal became to leverage these models as ultimate tools to enhance productivity, competitiveness, and customer experience across diverse sectors.

With ChatGPT paving the way, a broad range of organizations and professionals are exploring how to integrate GenAI into workflows and solutions. The widespread interest and investment have underscored the technology’s transformative potential and laid the groundwork for its continued evolution in the years to come.

4 Uses Cases for GenAI in Manufacturing

In manufacturing organizations, the utilization of GenAI-powered tools and solutions is primarily focused on four key areas:

1. Content Generation: This includes automated report generation, in which GenAI algorithms are employed to automatically generate reports based on predefined parameters and data inputs.
2. User Interface Enhancement: This involves the integration of chatbots into user interfaces, enabling more intuitive and interactive communication between users and systems.
3. Knowledge Management: GenAI facilitates knowledge management by providing co-pilot services that help users access and interpret vast amounts of data and information.
4. Software and Delivery: This encompasses various applications, such as code generation, in which GenAI is leveraged to automate the creation of software code, streamlining development processes.

According to IDC’s GenAI ARC Survey of 2023, manufacturing organizations are actively evaluating or implementing GenAI solutions.

Around 30% of European respondents have already invested significantly in GenAI, with spending plans established for training, acquiring Gen AI-enhanced software, and consulting. Nearly 20% are doing some initial testing of models and focused proofs of concept, but don’t yet have a spending plan in place.

These results suggest steady growth in the adoption of GenAI-powered tools and solutions within the manufacturing sector. The initial hype surrounding GenAI in 2023, fueled by its perceived potential as a “wonder technology,” has evolved into a pragmatic recognition of its capacity to address ongoing challenges such as workforce shortages, skills gaps, language barriers, data complexity, regulatory compliance, and more.

In the manufacturing industry, GenAI is increasingly viewed as an enabling technology capable of facilitating innovation and overcoming barriers to success.

Framework for Manufacturing Organizations to Implement GenAI

To fully capitalize on the potential of GenAI pilots, manufacturing organizations recognize the need for comprehensive frameworks that encompass processes and policies. Key measures include:

• Data Sharing and Operations Practices: Organizations should prioritize the implementation of practices that ensure data integrity for LLMs developed internally or in collaboration with third parties. This ensures that data used in GenAI models is accurate, reliable, and ethically sourced.
• Corporate-Wide Guidelines for Transparency: Guidelines should be established to evaluate transparency and track the use of GenAI code, data, and trained models throughout the organization. This promotes accountability in GenAI usage.
• Mandatory GenAI Awareness and Acceptable Use Training Programs: Mandatory training programs should be implemented to raise awareness of GenAI capabilities and ethical considerations among designated workforce groups. This helps ensure that employees understand how to responsibly utilize GenAI technologies.

As excitement over the capabilities of GenAI has died down, organizations are becoming increasingly aware of the risks posed by potential intellectual property theft and privacy threats linked to the technology.

To address these concerns, many organizations are prioritizing the establishment or expansion of formal AI governance/ethics/risks councils tasked with overseeing the ethical use of GenAI and mitigating risks associated with privacy, manipulation, bias, security, and transparency.

As a manufacturing interviewee in one of my studies put it, “The governance framework is indispensable in ensuring responsible and ethical AI implementation.” This underscores the importance of implementing robust governance measures to ensure the ethical use of GenAI within manufacturing organizations.

Deployment Strategies

Strategies for selecting the right solution for the right use case can vary substantially. A global white goods company, for example, piloted several GenAI-powered use cases in 2023. Its selection and deployment strategy encompassed a range of approaches, including:

• Off-the-Shelf Solutions: The company utilized ready-to-use, commercially available GenAI-embedded software-as-a-service solutions. These offered immediate access to GenAI capabilities without the need for extensive development or customization.
• AI Assistants: It deployed AI assistants to support specific tasks within their business processes. These assistants helped, for example, to create designs based on predetermined workflows, providing valuable support and efficiency gains.
• AI Agents: The company deployed AI agents in complex use cases requiring the orchestration of workflows and decision-making based on AI-driven insights. The agents leveraged GenAI to analyze data and make informed decisions autonomously.

A primary challenge often mentioned in such endeavors is selecting the optimal LLM for company-specific use cases from a multitude of possibilities. With new models and solutions constantly emerging and becoming accessible, this task can be daunting. The selection process typically involves thorough market research, vendor presentations, and internal discussions about the technology framework underlying current and future use cases.

However, the success of GenAI ultimately hinges on the quality and quantity of the data utilized. Curating a diverse and sufficient data set is critical to ensuring unbiased outcomes and maximizing the effectiveness of GenAI solutions. Data curation therefore remains a cornerstone of success in leveraging GenAI technologies.

The Bottom Line

GenAI-powered technology holds immense potential across industries and regions, offering capabilities that traditional machine learning algorithms or neural networks may struggle to match in terms of breadth and depth. GenAI can assist in co-piloting humans, thereby addressing challenges associated with an aging and/or unqualified workforce.

However, organizations must prioritize addressing concerns such as data leakage, biases, and maintaining sovereignty over IT processes running in the background. These issues must be carefully managed to ensure the responsible and ethical implementation of this powerful technology.