History

Re-Envisioned Pacific: Japan Strategies for Post-Pearl Harbor Victory

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By Alex Crosby

Following the attack on Pearl Harbor, Japan’s options for attaining a favorable war termination diminished to a handful of feasible strategies. The United States, emboldened by the surprise bloodshed, committed to an unlimited war with Japan unless de-escalation or a viable forced negotiations option were presented.1 Japan did not pursued several alternative strategies to achieve a favorable outcome in its war against the United States. First, Japan possessed the ability to prevent attrition of critical wartime capabilities, including aviation assets and merchant shipping, but did not preserve critical combat power. Second, Japan did not sufficiently concentrated its combat power towards exploiting strategically beneficial offensives before the end of 1942. Finally, Japan underutilized its diplomatic and information means of national power. If Japan employed these alternative strategies, American’s willingness for war termination negotiations and the chances of Japan achieving its strategic objectives would have increased.

Preventing Attrition of Critical Wartime Capabilities

By preventing overwhelming attrition of its critical wartime capabilities, especially in the early stages of the war, Japanese could have applied its combat power to induce the United States to a negotiated war termination.2 Following the attack on Pearl Harbor and through the end of 1942, the United States shifted its focus to a theater-wide defensive posture while reconstituting and repositioning its combat power needed to confront Japan. America’s posture its forces for a campaign of cumulative attrition, allowing US forces to maintain the initiative and conduct systematic engagements to impose unsustainable military losses on Japan.

However, the American effort relied on friendly local forces alienated by the brutal Japanese occupations providing intelligence of Japanese force movements. This tactical intelligence proved fundamental for the attrition of Japanese aircraft and pilots traveling between Rabaul and Guadalcanal, eroding Japanese air combat power.3 Japan’s did not focus on limiting their intelligence flow from alienated civilians, either through coercive or forceful means, to prevent attrition of its critical land-based aviation and pilots. Likewise, Japan did not sufficiently collect and exploit intelligence about the United States as it had during the first few months following Pearl Harbor to ensure naval aviation maintained combat loss mitigated initiatives.4

To further mitigate losses of its land and naval aviation capabilities Japan needed to focus on resource reallocation, pilot recovery operations, and maintaining aviation proficiency. After the initial offensives of 1941 and 1942, Japan depleted its aviation assets to dangerously low levels with no clear path for reconstitution. To prevent crippling attrition, Japan could have provided long-distance air support from Rabaul for the south Pacific. In addition, Japan was slow to recognize the future operational demand for greater quantities of its aviation assets and shift resources from obsolete programs like the superbattleship program.5

Finally, Japan’s inability to avoid detrimental losses of its proficient pilots by focusing on pilot recovery operations and rotating pilots to instruct recruits proved costly.6,7 At war initiation, Japan possessed a cadre of talented pilots. Japan’s failure to prioritized maintaining the cadre of skilled pilots negated their advantage they held at the start of the war. By capitalizing on early airpower concentrations and avoiding attrition of such a critical intellectual capability, Japan would have sustain its continued offensives with devastating efficacy and forced the United States to the bargaining table.8

The little attention paid to the protection of Japanese merchant shipping proved costly, as this non-military power was attrited to fatal levels and counted the early war American strategy of cumulative attrition.9 The tyranny of distance in the Pacific required significant quantities of merchant shipping to maintain the extensive sea lines of communications.10 Although Japan remained unaware, the United States had decrypted Japan’s merchant shipping communications. Japan did not appreciate the level of risk that existed and did not change its encryption following its attack on Pearl Harbor. This protection of vital communications would have blunted the American intelligence interception and decreased the Japanese merchant shipping attrition levels.11 American submarines posed the great threat to Japanese merchant shipping, but Japan was slow to recognize the threat and reallocate resources to convoy escorts and anti-submarine tactics.12 These ship-based efforts, coupled with land and naval aviation, would have preserved Japanese logistics and transportation capabilities for the necessary offensives to force the negotiated end of hostilities.13

Concentration of Combat Power for Strategic Offensives

Japan’s failure to concentrate its offensive combat early in the war to achieve decisive victories decreased the United States’ willingness to negotiate. In the early stages of conflict with the United States, an underlying aspect of Japanese wartime execution was a risk-averse approach to offensives. This piecemeal mindset led to debilitating attrition, such as the slow commitment to capturing and defending Guadalcanal.14 Rather than the piecemeal approach, Japan could have concentrated overwhelming force to attack the American forces and push eastwards through the Central Pacific.15 Overwhelming force coupled with Japan’s distinct naval warfare advantages could have proven decisive. The Japanese navy missed an opportunity to continued its fearsome offensives under cover of darkness and using sea control during the daytime.16

Japan did not focus its offensive combat power in bolder ways to achieve decisive action with strategic benefits. One operational line of efforts planned for but never executed was the use of Japanese submarines in the vicinity of Hawaii to sink American ships entering and leaving the port.17 This use of Japanese submarines, especially immediately following the attack on Pearl Harbor, would have crippled America ships and the limited aircraft carriers returning to port.

Japan did not concentrate its defensive combat power through the garrisoning of mutually supportive islands, a miscalculation American forces exploited. The isolated citadel strategy with its island defenses proved vulnerable to the American leapfrogging approach.18 Vast distances between these islands were often equivalent to the coast-to-coast span of the United States and placed a tremendous strain on supply chains, resulting in non-combat-related losses for aircraft.19 Concentrating defensive combat power on mutually supportive islands, Japan could then bring to bear overwhelming firepower to deter American invasion plans or repel landing assaults.20 The practical approach to amphibious defensive warfare could have allowed for the coordination of simultaneous attacks on approaching American naval forces and limited the attrition of critical Japanese air power.21,22 The coordination of firepower from these mutually supportive islands, in the form of fixed artillery sites and land-based aviation, could have undermined American strategy and provided more effective safe havens for reconstituting Japanese forces.

With the concentration of offensive and defensive combat power, Japan did not launch audacious offensives before the end of 1942, which would have resulting in the decisive destruction of American naval forces. At the outset of the war, Japanese leadership recognized the industrial might of the United States would inevitably lead to defeat unless Japan could meet its principal military aims before the end of 1942.23,24,25,26 These bold offensives would have denied the United States strategic positions required for force projection, such as Guadalcanal, and disrupted vulnerable sea lines of communication. 27 Japanese offensives should have targeted Ceylon and Australia to threaten Allied capabilities to support American force movements and draw American carriers, still few in numbers and lacking proven doctrine, to more threatening operating areas. 28,29 The Indian Ocean would have been an area of strategic gain for Japan should it have employed its submarine force, away from Allied air cover, to conduct convoy raiding on Lend-Lease merchant vessels transiting to support Russia via the Middle East.30,31 Most significantly, Japan should have executed its planned invasion of Hawaii, which would have directly threatened Alaska, the West Coast, and the Panama Canal.32,33 These three locations were of particular concern for the United States, while increasing their willingness to negotiate a peace settlement.34

Employing Diplomatic and Information Means

Aside from preventing attrition and concentrating combat power, Japan did not exploit its diplomatic and information leverage to force negotiations with the United States. The United States remains concerned about Japan’s involvement within the Tripartite Pact. Japan could have exploited this opportunity by quickly pulling out of the Tripartite Pact after Pearl Harbor to unburden itself from the disjointed German and Italian war aims.35 The Tripartite Pact forced Japan into close relations with Germany and Italy, both had their own strategic objectives and were so distanced that any significant resource or military assistance to Japan was impractical.36 By distancing itself diplomatically from Germany and Italy, Japan could have vastly complicated President Roosevelt’s strategic calculus for publicly justifying the war in Europe to the American people. 37 A rapid exit from the Tripartite Pact would have negated the risk of Germany and Italy declaring war on the United States, which bolstered the American public’s emotions for hatred and revenge.38

Japanese exploitation of divisions within the Allies, either via diplomatic or information means, could have also proved beneficial for several reasons. First, China was a significant cause of manpower attrition for the Japanese, aggravated by the increasing influx of Allied military assistance.39 If Japan could have diplomatically severed this assistance, it could have detracted the Allied political interest within the region and ensured Japan’s status as the regional hegemony. Second, a point of possible exploitation could have been isolating Australia and India diplomatically from Great Britain by highlighting the ongoing colonial ambitions of Winston Churchill. Australia, India, and to a lesser extent, smaller Asian countries, had existing ambitions to separate themselves from Great Britain.40 Japan should have exploited these divisions and fractured British equities, which would have decreased the political interest in the region.

Japan should have highlighted the forcefulness of American leadership over Allied strategy and policy. This messaging should have sought to use American aggressiveness over its allies as a rationale for degrading the United States’ access to critical military facilities in the south and central Pacific.41 With distinct divisions amongst the Allies, Japan should have exploited opportunities to fracture away as much support for the United States as possible.

Although Japan used propaganda to a limited extent against deployed American forces, Japan did not sufficiently target the domestic American population. During the early stages of the war, Japan used propaganda as a leading tool of its national strategy with strategic success.42 Japan missed an opportunity to wield this capability with devastating effects by highlighting perceived British ambitions to expand its colonial rule against southeast Asian nations.43 Additionally, Japan did not highlight the enormous financial costs of General MacArthur’s self-imposed Philippine Campaign, which could eroded the American public’s support against any continued intervention in the Philippines.44,45

Japan did not focus on weakening the American public’s view of the Pacific Fleet serving as a mobile defensive line early in the war. By messaging the Pacific Fleet as an ineffective deterrent fleet incapable of preventing further Japanese aggression, combined with a decisive attack, would have potentially dissolved the America public’s belief in the West Coast’s safety.46 This emphasis on diminishing the morale of the American people could have been a focal point of Japanese strategy to circumvent the domestic calls for total national unity.47 With the will of the American people depleted, the chances of a negotiated war termination would have likely increased in Japan’s favor.

Counterargument and Rebuttal

Some might argue that the Japanese wait-and-react strategy served as a better solution for ensuring a favorable outcome with the United States. This strategy was structured to combine phased combat actions to achieve the complete destruction of American naval power in the Pacific Ocean. First, Japanese naval forces would search for and annihilate American naval forces permanently stationed or operating in the western Pacific Ocean. Next, Japan would conduct a series of minor naval engagements to attrite an American main battle force moving westward to relieve or recapture American territories like Guam. Finally, Japan would seek to decisive engagement, decimate the American naval forces to force negotiations for war termination.48

The attack on Pearl Harbor, and the initial stages of the war, shaped by strategic assumptions fundamental to the wait-and-react strategy remained valid throughout the Interwar Period. First, the Japanese assumed it would achieve its war aim following a rapid, decisive offensives, forcing the United States into peace negotiations. Second, the Japanese navy’s was to gain sea control needed for conflict success, enabling the capture of a strategic position essential for the survival of Japan following the war, and ensure the future prosperity of Japan. In the minds of the Japanese, the western and central Pacific were the defining features of these geographic considerations. Third, Japanese navy leadership remained adamant that only decisively defeating the American battle fleet guaranteed sea control. Fourth, suppose if Japan could not confront the United States with equal or greater numbers of ships. In that case, Japan could negate with ship overmatch with superior firepower, armor, training, and outranging technology such as carrier-borne aviation. Finally, the victory following a decisive naval battle would ensure the Japanese homeland security needed for prosperity and lead directly to a negotiated peace with the United States.49

Despite these contrary views, the wait-and-react strategy was a doomed path for Japan to remain on without considering alternative strategies that would have better enabled a negotiated war termination with the United States. A significant piece of evidence for this is that Japan blatantly violated its own fundamental axiom of grand strategy, which was the principle of fighting only one enemy at a time.50 Additionally, key Japanese naval leadership, including Yamamoto Isoroku, Ozawa Jisaburo, and Onishi Takijiro, guarded criticisms for the wait-and-react strategy. First, it relied entirely on the United States being a cooperative adversary and left the initiative of location and time for naval engagement with the Pacific Fleet. Second, the nature of offensive naval power had transitioned from the battleship-based fleet to one reliant on carrier-based aviation: a transition that required a more risk-averse (and thus less offensive) mindset to prevent loss of expensive carriers that would be troublesome to reconstitute during the conflict.

Finally, even with the introduction of carriers, the confrontation between Japan and the United States would still ultimately focus on critical airbases and facilities, predominately throughout the central Pacific.51 To rationalize both these criticisms and the fundamental tenets of wait-and-react, the Japanese navy sought a carrier aviation-based pre-emptive strike deep at Pearl Harbor to decisively defeat the Pacific Fleet. However, no legitimate plan was devised to transition to war termination through a negotiated settlement. 52 This execution of wait-and-react military strategy without the diplomatic ammunition to support it left Japan in a precarious situation that slowly but surely, led to Japan’s defeat.

Lieutenant Commander Crosby, an active duty naval intelligence officer, began his career as a surface warfare officer. His assignments have included the USS Lassen (DDG-82), USS Iwo Jima (LHD-7), U.S. Seventh Fleet, and the Office of Naval Intelligence, with multiple deployments supporting naval expeditionary and special warfare commands. He is a Maritime Advanced Warfighting School–qualified maritime operational planner and an intelligence operations warfare tactics instructor. He holds master’s degrees from the American Military University and the Naval War College.

Endnotes

1. Paine, Sarah C. M. The Wars for Asia, 1911-1949. New York: Cambridge University Press, 2012. 189.

2. Lee, Bradford A. “A Pivotal Campaign in a Peripheral Theatre: Guadalcanal and World War II in the Pacific.” In Naval Power and Expeditionary Warfare: Peripheral Campaigns and New Theatres of Naval Warfare. Bruce A. Elleman and S. C. M. Paine, eds. London and New York: Routledge, 2011. 84.

3. Ibid., 94.

4. Evans, David C. and Mark R. Peattie. Kaigun: Strategy, Tactics, and Technology in the Imperial Japanese Navy, 1887-1941. Annapolis: Naval Institute Press, 1997. 470-471.

5. Warner, Denis and Peggy. “The Doctrine of Surprise”; Miller, Edward S. “Kimmel’s Hidden Agenda”; and Cohen, Eliot A. “The Might-Have-Beens of Pearl Harbor.” MHQ: The Quarterly Journal of Military History, vol. 4, no. 1 (autumn 1991). 23.

6. O’Brien, Phillips. How the War Was Won: Air-Sea Power and Allied Victory in World War II. Cambridge: Cambridge University Press, 2015. 385.

7. Baer, George W. One Hundred Years of Sea Power: The U.S. Navy, 1890-1990. Stanford: Stanford University Press, 1994. 221.

8. O’Brien, Phillips. How the War Was Won: Air-Sea Power and Allied Victory in World War II. Cambridge: Cambridge University Press, 2015. 375.

9. Wylie, J. C. Appendix A, “Excerpt from ‘Reflections on the War in the Pacific.’” In Military Strategy: A General Theory of Power Control. New Brunswick: Rutgers University Press, 1967. Annapolis: Naval Institute Press, reprint, 1989. 119.

10. James, D. Clayton. “American and Japanese Strategies in the Pacific War.” In Makers of Modern Strategy: From Machiavelli to the Nuclear Age. Peter Paret, ed. Princeton: Princeton University Press, 1986. 717.

11. Ibid., 729.

12. O’Brien, Phillips. How the War Was Won: Air-Sea Power and Allied Victory in World War II. Cambridge: Cambridge University Press, 2015. 417.

13. Evans, David C. and Mark R. Peattie. Kaigun: Strategy, Tactics, and Technology in the Imperial Japanese Navy, 1887-1941. Annapolis: Naval Institute Press, 1997. 485.

14. James, D. Clayton. “American and Japanese Strategies in the Pacific War.” In Makers of Modern Strategy: From Machiavelli to the Nuclear Age. Peter Paret, ed. Princeton: Princeton University Press, 1986. 718.

15. Lee, Bradford A. “A Pivotal Campaign in a Peripheral Theatre: Guadalcanal and World War II in the Pacific.” In Naval Power and Expeditionary Warfare: Peripheral Campaigns and New Theatres of Naval Warfare. Bruce A. Elleman and S. C. M. Paine, eds. London and New York: Routledge, 2011. 88.

16. Ibid., 92.

17. Baer, George W. One Hundred Years of Sea Power: The U.S. Navy, 1890-1990. Stanford: Stanford University Press, 1994. 171.

18. Larrabee, Eric. Commander in Chief: Franklin Delano Roosevelt, His Lieutenants and Their War. New York: Simon and Schuster, 1987. Annapolis: Naval Institute Press, reprint, 2004. 339.

19. O’Brien, Phillips. How the War Was Won: Air-Sea Power and Allied Victory in World War II. Cambridge: Cambridge University Press, 2015. 409.

20. James, D. Clayton. “American and Japanese Strategies in the Pacific War.” In Makers of Modern Strategy: From Machiavelli to the Nuclear Age. Peter Paret, ed. Princeton: Princeton University Press, 1986. 718.

21 Ibid., 719.

22. Evans, David C. and Mark R. Peattie. Kaigun: Strategy, Tactics, and Technology in the Imperial Japanese Navy, 1887-1941. Annapolis: Naval Institute Press, 1997. 466.

23. Lee, Bradford A. “A Pivotal Campaign in a Peripheral Theatre: Guadalcanal and World War II in the Pacific.” In Naval Power and Expeditionary Warfare: Peripheral Campaigns and New Theatres of Naval Warfare. Bruce A. Elleman and S. C. M. Paine, eds. London and New York: Routledge, 2011. 88.

24. James, D. Clayton. “American and Japanese Strategies in the Pacific War.” In Makers of Modern Strategy: From Machiavelli to the Nuclear Age. Peter Paret, ed. Princeton: Princeton University Press, 1986. 707-708.

25. Baer, George W. One Hundred Years of Sea Power: The U.S. Navy, 1890-1990. Stanford: Stanford University Press, 1994. 159.

26. Ibid., 169.

27. Lee, Bradford A. “A Pivotal Campaign in a Peripheral Theatre: Guadalcanal and World War II in the Pacific.” In Naval Power and Expeditionary Warfare: Peripheral Campaigns and New Theatres of Naval Warfare. Bruce A. Elleman and S. C. M. Paine, eds. London and New York: Routledge, 2011. 84-85.

28. Ibid., 86-87.

29. O’Brien, Phillips. How the War Was Won: Air-Sea Power and Allied Victory in World War II. Cambridge: Cambridge University Press, 2015. 391.

30. Ibid., 418.

31. Baer, George W. One Hundred Years of Sea Power: The U.S. Navy, 1890-1990. Stanford: Stanford University Press, 1994. 209.

32. Larrabee, Eric. Commander in Chief: Franklin Delano Roosevelt, His Lieutenants and Their War. New York: Simon and Schuster, 1987. Annapolis: Naval Institute Press, reprint, 2004. 364-365.

33. Baer, George W. One Hundred Years of Sea Power: The U.S. Navy, 1890-1990. Stanford: Stanford University Press, 1994. 210.

34. “The Blue Team: Documents on U.S. Policy, Strategy, and Operation1949. New York: Cambridge University Press, 2012. 186.

35. Evans, David C. and Mark R. Peattie. Kaigun: Strategy, Tactics, and Technology in the Imperial Japanese Navy, 1887-1941. Annapolis: Naval Institute Press, 1997. 454.s in the Pacific War.” 11.

36. Paine, Sarah C. M. The Wars for Asia, 1911-

37. James, D. Clayton. “American and Japanese Strategies in the Pacific War.” In Makers of Modern Strategy: From Machiavelli to the Nuclear Age. Peter Paret, ed. Princeton: Princeton University Press, 1986. 712-713.

38. Baer, George W. One Hundred Years of Sea Power: The U.S. Navy, 1890-1990. Stanford: Stanford University Press, 1994. 181.

39. James, D. Clayton. “American and Japanese Strategies in the Pacific War.” In Makers of Modern Strategy: From Machiavelli to the Nuclear Age. Peter Paret, ed. Princeton: Princeton University Press, 1986. 713, 716.

40. Paine, Sarah C. M. The Wars for Asia, 1911-1949. New York: Cambridge University Press, 2012. 198.

41. James, D. Clayton. “American and Japanese Strategies in the Pacific War.” In Makers of Modern Strategy: From Machiavelli to the Nuclear Age. Peter Paret, ed. Princeton: Princeton University Press, 1986. 723.

42. Ibid., 719-720.

43. Ibid., 722.

44. O’Brien, Phillips. How the War Was Won: Air-Sea Power and Allied Victory in World War II. Cambridge: Cambridge University Press, 2015. 382.

45. Larrabee, Eric. Commander in Chief: Franklin Delano Roosevelt, His Lieutenants and Their War. New York: Simon and Schuster, 1987. Annapolis: Naval Institute Press, reprint, 2004. 346.

46. Baer, George W. One Hundred Years of Sea Power: The U.S. Navy, 1890-1990. Stanford: Stanford University Press, 1994. 150.

47. Warner, Denis and Peggy. “The Doctrine of Surprise”; Miller, Edward S. “Kimmel’s Hidden Agenda”; and Cohen, Eliot A. “The Might-Have-Beens of Pearl Harbor.” MHQ: The Quarterly Journal of Military History, vol. 4, no. 1 (autumn 1991). 22.

48. Evans, David C. and Mark R. Peattie. Kaigun: Strategy, Tactics, and Technology in the Imperial Japanese Navy, 1887-1941. Annapolis: Naval Institute Press, 1997. 464.

49. Ibid., 480.

50. Ibid., 450.

51. Ibid., 472.

52. Warner, Denis and Peggy. “The Doctrine of Surprise”; Miller, Edward S. “Kimmel’s Hidden Agenda”; and Cohen, Eliot A. “The Might-Have-Beens of Pearl Harbor.” MHQ: The Quarterly Journal of Military History, vol. 4, no. 1 (autumn 1991). 25.

Featured Image: October 1941, Imperial Japanese Navy carrier Zuikaku at Bungo-channel. (Photo colorized by Irootoko Jr.)

Future Tech

Grassroots AI: Driving Change in the Royal Navy with Workflow

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By Francis Heritage

Introduction

In September 2023, the Royal Navy (RN) advertised the launch of the Naval AI Cell (NAIC), designed to identify and advance AI capability across the RN. NAIC will act as a ‘transformation office’, supporting adoption of AI across RN use cases, until it becomes part of Business as Usual (BaU). NAIC aims to overcome a key issue with current deployment approaches. These usually deploy AI as one-off transformation projects, normally via innovation funding, and often result in project failure. The nature of an ‘Innovation Budget’ means that when the budget is spent, there is no ability to further develop, or deploy, any successful Proof of Concept (PoC) system that emerged.

AI is no longer an abstract innovation; it is fast becoming BaU, and it is right that the RN’s internal processes reflect this. Culturally, it embeds the idea that any AI deployment must be both value-adding and enduring. It forces any would-be AI purchaser to focus on Commercial Off The Shelf (COTS) solutions, significantly reducing the risk of project failure, and leveraging the significant investment already made by AI providers.

Nevertheless, NAIC’s sponsored projects still lack follow-on budgets and are limited in scope to just RN-focused issues. The danger still exists that NAIC’s AI projects fail to achieve widespread adoption, despite initial funding; a common technology-related barrier, known as the ‘Valley of Death.’ In theory, there is significant cross-Top Line Budget (TLB) support to ensure the ‘Valley’ can be bridged. The Defense AI and Autonomy Unit within MOD Main Building is mandated to provide policy and ethical guidance for AI projects, while the Defense Digital/Dstl Defense AI Centre (DAIC) acts as a repository for cross-MOD AI development and deployment advice. Defense Digital also provides most of the underlying infrastructure required for AI to deploy successfully. Known by Dstl as ‘AI Building Blocks’, this includes secure cloud compute and storage in the shape of MODCloud (in both Amazon Web Service and Microsoft Azure) and the Defense Data Analytics Portal (DDAP), a remote desktop of data analytics tools that lets contractors and uniformed teams collaborate at OFFICIAL SENSITIVE, and accessible via MODNet.

The NAIC therefore needs to combine its BaU approach with other interventions, if AI and data analytics deployment is to prove successful, namely:

  • Create cross-TLB teams of individuals around a particular workflow, thus ensuring a larger budget can be brought to bear against common issues.
  • Staff these teams from junior ranks and rates, and delegate them development and budget responsibilities.
  • Ensure these teams prioritize learning from experience and failing fast; predominantly by quickly and cheaply deploying existing COTS, or Crown-owned AI and data tools. Writing ‘Discovery Reports’ should be discouraged.
  • Enable reverse-mentoring, whereby these teams share their learnings with Flag Officer (one-star and above) sponsors.
  • Provide these teams with the means to seamlessly move their projects into Business as Usual (BaU) capabilities.

In theory this should greatly improve the odds of successful AI delivery. Cross-TLB teams should have approximately three times the budget to solve the same problem, when compared to an RN-only team. Furthermore, as the users of any developed solution, teams are more likely to buy and/or develop systems that work and deliver value for money. With hands-on experience and ever easier to deploy COTS AI and data tools, teams will be able to fail fast and cheaply, and usually at a lower cost than employing consultants. Flag Officers providing overarching sponsorship will receive valuable reverse-mentoring; specifically understanding first-hand the disruptive potential of AI systems, the effort involved in understanding use-cases and the need for underlying data and infrastructure. Finally, as projects will already be proven and part of BaU, projects may be cheaper and less likely to fail than current efforts.

Naval AI Cell: Initial Projects

The first four tenders from the NAIC were released via the Home Office Accelerated Capability Environment (ACE) procurement framework in March 2024. Each tender aims to deliver a ‘Discovery’ phase, exploring how AI could be used to mitigate different RN-related problems.1 However, the nature of the work, the very short amount of time for contractors to respond, and relatively low funding available raises concern about the value for money they will deliver. Industry was given four days to provide responses to the tender, about a fifth of the usual time, perhaps a reflection of the need to complete projects before the end of the financial year. Additionally, the budget for each task was set at approximately a third of the level for equivalent Discovery work across the rest of Government.2 The tenders reflect a wide range of AI use-cases, including investigating JPA personnel records, monitoring pictures of rotary wing oil filter papers, and underwater sound datasets, each of which requires a completely different Machine Learning approach.

Figure 1: An example self-service AI Workflow, made by a frontline civilian team to automatically detect workers not wearing PPE. The team itself has labelled relevant data, trained and then deployed the model using COTS user interface. Source: V7 Labs.

Take the NAIC’s aircraft maintenance problem-set as an example. The exact problem (automating the examination of oil filter papers of rotary wing aircraft) is faced by all three Single Services. First, by joining forces with the RAF to solve this same problem, the Discovery budget could have been doubled, resulting in a higher likelihood of project success and ongoing savings. Second, by licensing a pre-existing, easy-to-use commercial system that already solves this problem, NAIC could have replaced a Discovery report, written by a contractor, with cheaper, live, hands-on experience of how useful AI was in solving the problem.3 This would have resulted in more money being available, and a cheaper approach being taken.

Had the experiment failed, uniformed personnel would have learnt significantly more from their hands-on experience than by reading a Discovery report, and at a fraction of the price. Had it succeeded, the lessons would have been shared across all three Services and improved the chance of success of any follow-on AI deployment across wider MOD. An example of a COTS system that achieves this is V7’s data labeling and model deployment system, available with a simple user interface; it is free for up to 3 people, or £722/month for more complex requirements.4 A low-level user experiment using this kind of platform is unlikely to have developed sufficient sensitive data to have gone beyond OFFICIAL.

Introducing ‘Workflow Automation Guilds’

Focusing on painful, AI-solvable problems, shared across Defense, is a good driver to overcome these stovepipes. Identification of these workflows has been completed by the DAIC and listed in the Defence AI Playbook.5 It lists 15 areas where AI has potential to deliver a step-change capability. Removing the problems that are likely to be solved by Large Language Models (where a separate Defence Digital procurement is already underway), leaves 10 workflows (e.g. Spare Parts Failure Prediction, Optimizing Helicopter Training etc) where AI automation could be valuably deployed.

However, up to four different organizations are deploying AI to automate these 10 workflows, resulting in budgets that are too small to result in impactful, recurring work; or at least, preventing this work from happening quickly. Cross-Front Line Command (FLC) teams could be created, enabling budgets to be combined to solve the same work problem they collectively face. In the AI industry, these teams are known as ‘Guilds’; and given the aim is to automate Workflows, the term Workflow Automation Guilds (WAGs) neatly sums up the role of these potential x-FLC teams.

Focus on Junior Personnel

The best way to populate these Guilds is to follow the lead of the US Navy (USN) and US Air Force (USAF), who independently decided the best way to make progress with AI and data is to empower their most junior people, giving them responsibility for deploying this technology to solve difficult problems. In exactly the same way that the RN would not allow a Warfare Officer to take Sea Command if they are unable to draw a propulsion shaft-line diagram, so an AI or data deployment program should not be the responsibility of someone senior who does not know or understand the basics of Kubernetes or Docker.6 For example, when the USAF created their ‘Platform One’ AI development platform, roles were disproportionately populated by lower ranks and rates. As Nic Chaillan, then USAF Chief Software Officer, noted:

“When we started picking people for Platform One, you know who we picked? A lot of Enlisted, Majors, Captains… people who get the job done. The leadership was not used to that… but they couldn’t say anything when they started seeing the results.”7

The USN takes the same approach with regards to Task Force Hopper and Task Group 59.1.8 TF Hopper exists within the US Surface Fleet to enable rapid AI/ML adoption. This includes enabling access to clean, labeled data and providing the underpinning infrastructure and standards required for generating and hosting AI models. TG 59.1 focuses on the operational deployment of uncrewed systems, teamed with human operators, to bolster maritime security across the Middle East. Unusually, both are led by USN Lieutenants, who the the USN Chief of Naval Operations called ‘…leaders who are ready to take the initiative and to be bold; we’re experimenting with new concepts and tactics.’9

Delegation of Budget Spend and Reverse Mentoring

Across the Single Services, relatively junior individuals, from OR4 to OF3, could be formed on a cross-FLC basis to solve the Defence AI Playbook issues they collectively face, and free to choose which elements of their Workflow to focus on. Importantly, they should deploy Systems Thinking (i.e. an holistic, big picture approach that takes into account the relationship between otherwise discrete elements) to develop a deep understanding of the Workflow in question and prioritize deployment of the fastest, cheapest data analytics method; this will not always be an AI solution. These Guilds would need budgetary approval to spend funds, collected into a single pot from up to three separate UINs from across the Single Services; this could potentially be overseen by an OF5 or one-star. The one-star’s role would be less about providing oversight, and more to do with ensuring funds were released and, vitally, receiving reverse mentoring from the WAG members themselves about the viability and value of deploying AI for that use case.

The RN’s traditional approach to digital and cultural transformation – namely a top-down, directed approach – has benefits, but these are increasingly being rendered ineffective as the pace of technological change increases. Only those working with this technology day-to-day, and using it to solve real-world challenges, will be able to drive the cultural change the RN requires. Currently, much of this work is completed by contractors who take the experience with them when projects close. By deploying this reverse-mentoring approach, WAG’s not only cheaply create a cadre of uniformed, experienced AI practitioners, but also a senior team of Flag Officers who have seen first-hand where AI does (or does not) work and have an understanding of the infrastructure needed to make it happen.

Remote working and collaboration tools mean that teams need not be working from the same bases, vital if different FLCs are to collaborate. These individuals should be empowered to spend multi-year budgets of up to circa. £125k. As of 2024, this is sufficient to allow meaningful Discovery, Alpha, Beta and Live AI project phases to be undertaken; allow the use of COTS products; and small enough to not result in a huge loss if the project (which is spread among all three Services to mitigate risk) fails.

Figure 2: An example AI Figure 2: An example AI Opportunity Mapping exercise, where multiple AI capabilities (represented by colored cards) are mapped onto different stages of an existing workflow, to understand where, if anywhere, use of AI could enable or improve workflow automation. Source: 33A AI.

WAG Workflow Example

An example of how WAGs could work is as follows, using the oil sample contamination example. Members of the RN and RAF Wildcat and Merlin maintenance teams collectively identify the amount of manpower effort that could be saved if the physical checking of lube oil samples could be automated. With an outline knowledge of AI and Systems Thinking already held, WAG members know that full automation of this workflow is not possible; but they have identified one key step in the workflow that could be improved, speeding up the entire workflow of regular helicopter maintenance. The fact that a human still needs to manually check oil samples is not necessarily an issue, as they identify that the ability to quickly prioritize and categorize samples will not cause bottlenecks elsewhere in the workflow and thus provides a return on investment.

Members of the WAG would create a set of User Stories, an informal, general description of the AI benefits and features, written from a users’ perspective. With the advice from the DAIC, NAIC, RAF Rapid Capability Office (RCO) / RAF Digital or Army AI Centre, other members of the team would ensure that data is in a fit state for AI model training. In this use-case, this would involve labeling overall images of contamination, or the individual contaminants within an image, depending on the AI approach to be used (image recognition or object detection, respectively). Again, the use of the Defence Data Analytics Portal (DDAP), or a cheap, third-party licensed product, provides remote access to the tools that enable this. The team now holds a number of advantages over traditional, contractor-led approaches to AI deployment, potentially sufficient to cross the Valley of Death:

  • They are likely to know colleagues across the three Services facing the same problem, so can check that a solution has not already been developed elsewhere.10
  • With success metrics, labelled data and user requirements all held, the team has already overcome the key blockers to success, reducing the risk that expensive contractors, if subsequently used, will begin project delivery without these key building blocks in place.
  • They have a key understanding of how much value will be generated by a successful project, and so can quickly ‘pull the plug’ if insufficient benefits arise. There is also no financial incentive to push on if the approach clearly isn’t working.
  • Alternatively, they have the best understanding of how much value is derived if the project is successful.
  • As junior Front-Line operators, they benefit directly from any service improvement, so are not only invested in the project’s success, but can sponsor the need for BaU funding to be released to sustain the project in the long term, if required.
  • If working with contractors, they can provide immediate user feedback, speeding up development time and enabling a true Agile process to take place. Currently, contractors struggle to access users to close this feedback loop when working with MOD.

Again, Flag Officer sponsorship of such an endeavor is vital. This individual can ensure that proper recognition is awarded to individuals and make deeper connections across FLCs, as required.

Figure 3: Defense Digital’s Defense Data Analytics Portal (DDAP) is tailor-made for small, Front-Line teams to clean and label their data and deploy AI services and products, either standalone or via existing, call-off contract contractor support.

Prioritizing Quick, Hands-on Problem Solving

WAGs provide an incentive for more entrepreneurial, digitally minded individuals to remain in Service, as it creates an outlet for those who wish to learn to code and solve problems quickly, especially if the problems faced are ones they wrestle with daily. A good example of where the RN has successfully harnessed this energy is with Project KRAKEN, the RN’s in-house deployment of the Palantir Foundry platform. Foundry is a low-code way of collecting disparate data from multiple areas, allowing it to be cleaned and presented in a format that speeds up analytical tasks. It also contains a low-level AI capability. Multiple users across the RN have taken it upon themselves to learn Foundry and deploy it to solve their own workflow problems, often in their spare time, with the result that they can get more done, faster than before. With AI tools becoming equally straightforward to use and deploy, the same is possible for a far broader range of applications, provided that cross-TLB resources can be concentrated at a junior level to enable meaningful projects to start.

Figure 4: Pre-existing Data/AI products or APIs, bought from commercial providers, or shared from elsewhere in Government, are likely to provide the fastest, cheapest route to improving workflows.11

Deploying COTS Products Over Tailored Services

Figure 4 shows the two main options available for WAGs when deploying AI or data science capabilities: Products or Services. Products are standalone capabilities created by industry to solve particular problems, usually made available relatively cheaply. Typically, COTS, they are sold on a per-use, or time-period basis, but cannot be easily tailored or refined if the user has a different requirement.

By contrast, Services are akin to a consulting model where a team of AI and Machine Learning engineers build an entirely new, bespoke system. This is much more expensive and slower than deploying a Product but means users should get exactly what they want. Occasionally, once a Service has been created, other users realize they have similar requirements as the original user. At this point, the Service evolves to become a Product. New users can take advantage of the fact that software is essentially free to either replicate or connect with and gain vast economies of scale from the initial Service investment.

WAGs aim to enable these economies of scale; either by leveraging the investment and speed benefits inherent in pre-existing Products or ensuring that the benefits of any home-made Services are replicated across the whole of the MOD, rather than remaining stove-piped or siloed within Single Services.

Commercial/HMG Off the Shelf Product. The most straightforward approach is for WAGs to deploy a pre-existing product, licensed either from a commercial provider, or from another part of the Government that has already built a Product in-house. Examples include the RAF’s in-house Project Drake, which has developed complex Bayesian Hierarchical models to assist with identifying and removing training pipeline bottlenecks; these are Crown IP, presumably available to the RN at little-to-no cost, and their capabilities have been briefed to DAIC (and presumably briefed onwards to the NAIC).

Although straightforward to procure, it may not be possible to deploy COTS products on MOD or Government systems, and so may be restricted up to OFFICIAL or OFFICIAL SENSITIVE only. Clearly, products developed or deployed by other parts of MOD or National Security may go to higher classifications and be accessible from MODNet or higher systems. COTS products are usually available on a pay-as-you-go, monthly, or user basis, usually in the realm of circa £200 per user, per month, providing a fast, risk-free way to understand whether they are valuable enough to keep using longer-term.

Contractor-supported Product. In this scenario, deployment is more complex; for example, the product needs to deploy onto MOD infrastructure to allow sensitive data to be accessed. In this case, some expense is required, but as pre-existing COTS, the product should be relatively cheap to deploy as most of the investment has already been made by the supplier. This option should allow use up to SECRET but, again, users are limited to those use-cases offered by the commercial market. These are likely to be focused on improving maintenance and the analysis of written or financial information. The DAIC’s upcoming ‘LLMs for MOD’ project is likely to be an example of a Contractor-supported Product; MOD users will be able to apply for API access to different Large Language Model (LLM) products, hosted on MOD infrastructure, to solve their use-cases. Contractors will process underlying data to allow LLMs to access it, create the API, and provide ongoing API connectivity support.

Service built in-house. If no product exists, then there is an opportunity to build a low-code solution in DDAP or MODCloud and make it accessible through an internal app. Some contractor support may be required, particularly to provide unique expertise the team cannot provide themselves (noting that all three Services may have Digital expertise available via upcoming specialist Reserve branches, with specialist individuals available at a fraction of the cost of their civilian equivalent day rates).12 Defense Digital’s ‘Enhanced Data Teams’ service provides a call-off option for contractors to do precisely this for a short period of time. It is likely that these will not, initially, deploy sophisticated data analysis or AI techniques, but sufficient value may be created with basic data analytics. In any event, the lessons learnt from building a small, relatively unsophisticated in-house service will provide sufficient evidence to ascertain whether a full, contractor-built AI service will provide value for money, if built. Project Kraken is a good example of this; while Foundry is itself a product and bought under license, it is hosted in MOD systems and allows RN personnel to build their own data services within it.

Service built by contractors. These problems are so complex, or unique to Defense, that no COTS product exists. Additionally, the degree of work is so demanding that Service Personnel could not undertake this work themselves. In this case, WAGs should not be deployed. Instead, these £100k+ programs should remain the purview of Defense Digital or the DAIC and aim to instead provide AI Building Blocks that empower WAGs to do AI work. In many cases, these large service programs provide cheap, reproducible products that the rest of Defense can leverage. For example, the ‘LLMs for MOD’ Service will result in relatively cheap API Products, as explained above. Additionally, the British Army is currently tendering for an AI-enabled system that can read the multiple hand-and-type-written text within the Army archives. This negates the need for human researchers to spend days searching for legally required records that can now be found in seconds. Once complete, this system could offer itself as a Product that can ingest complex documents from the rest of the MOD at relatively low cost. This should negate the need for the RN to pay their own 7-figure sums to create standalone archive scanning services. To enable this kind of economy of scale, NAIC could act as a liaison with these wider organizations. Equipped with a ‘shopping list’ of RN use cases, it could quickly deploy tools purchased by the Army, RAF or Defense Digital across the RN.

Finding the Time

How can WAG members find the time to do the above? By delegating budget control down to the lowest level, and focusing predominantly on buying COTS products, the amount of time required should be relatively minimal; in essence, it should take the same amount of time as buying something online. Some work will be required to understand user stories and workflow design, but much of this will already be in the heads of WAG members. Imminent widespread MOD LLM adoption should, in theory, imminently reduce the amount of time spent across Defense on complex, routine written work (reviewing reports, personnel appraisals, post-exercise or deployment reports or other regular reporting).13 This time could be used to enable WAGs to do their work. Indeed, identifying where best to deploy LLMs across workflows are likely to be the first roles of WAGs, as soon as the ‘LLMs for MOD’ program reaches IOC. Counter-intuitively, by restricting the amount of time available to do this work, it automatically focuses attention on solutions that are clearly valuable; solutions that save no time are, by default, less likely to be worked on, or have money spent on them.

Conclusions

The RN runs the risk of spreading the NAIC’s budget too thinly, in its attempt to ‘jumpstart’ use of AI across Business as Usual disciplines. By contrast, users should be encouraged to form Workflow Automation Guilds across FLCs. Supported by a senior sponsor, knowledgeable members of the Reserves, the NAIC and one-on-one time with the DAIC, WAGs could instead focus on the COTS solution, or pre-existing Crown IP, that will best solve their problem. Budget responsibilities should be delegated down too, thereby enabling access to existing, centralized pools of support, such as the Enhanced Data Teams program, DDAP, or the upcoming ‘LLMs for MOD’ API Service. In this way, projects are more likely to succeed, as they will have demonstrated value from the very start and will have been co-developed by the very users that deploy them. The speed at which AI and data services are becoming easier to use is reflected by the RN’s Kraken team, while the need to trust low-level officers and junior rates is borne out by the success currently being enjoyed by both the USAF and USN with their own complex AI deployments.

Prior to leaving full-time service, Lieutenant Commander Francis Heritage, Royal Navy Reserve, was a Principal Warfare Officer and Fighter Controller. Currently an RNR GW officer, he works at the Defence arm of Faculty, the UK’s largest independent AI company. LtCdr Francis is now deployed augmenting Commander United Kingdom Strike Force (CSF).

The views expressed in this paper are the author’s, and do not necessarily represent the official views of the MOD, the Royal Navy, RNSSC, or any other institution.

References

1. Discovery’ is the first of 5 stages in the UK Government Agile Project Delivery framework, and is followed by Alpha, Beta, Live and Retirement. Each stage is designed to allow the overall program to ‘fail fast’ if it is discovered that benefits will not deliver sufficient value.

2. Author’s observations.

3. Volvo and the US commodities group Bureau Veritas both have Commercial off the Shelf products available for solving this particular problem.

4. Source: https://www.v7labs.com/pricing accessed 10 Apr 2024.

5. Source: https://assets.publishing.service.gov.uk/media/65bb75fa21f73f0014e0ba51/Defence_AI_Playbook.pdf

6. AI systems rely on machine learning frameworks and libraries; Docker packages these components together into reproducible ‘containers’, simplifying deployment. Kubernetes builds on Docker, providing an orchestration layer for automating deployment and management of containers over many machines.

7. Defence Unicorns podcast, 5 Mar 2024.

8. Source: Navy’s new ‘Project OpenShip’ aims to swiftly apply AI to data captured by vessels at sea | DefenseScoop.

9. https://www.afcea.org/signal-media/navys-junior-officers-lead-way-innovation.

10. The author knows of at least 3 AI projects across MOD aimed at automating operational planning and another 3 aiming to automate satellite imagery analysis.

11. API stands for Application Programming Interface, a documented way for software to communicate with other software. By purchasing access to an API (usually on a ‘per call’ or unlimited basis) a user can take information delivered by an API and combine it with other information before presenting it to a user. Examples include open-source intelligence, commercial satellite imagery, meteorological data, etc. 

12. Army Reserve Special Group Information Service, RNR Information Exploitation Branch and RAF Digital Reserves Consultancy. RNR IX and RAFDRC are both TBC.

13. Worldwide, Oliver Wyman estimates Generative AI will save an average of 2 hours per person per week; likely to be higher for office-based roles: https://www.oliverwymanforum.com/content/dam/oliver-wyman/ow-forum/gcs/2023/AI-Report-2024-Davos.pdf p.17.

Featured Image: The Operations Room of the carrier HMS Queen Elizabeth during an exercise in 2018. (Royal Navy photo)

Podcast

Sea Control 553 – Tracks on the Ocean with Dr. Sara Caputo

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By Jared Samuelson

Dr. Sara Caputo joins the program to discuss her new book, Tracks on the Ocean: A History of Trailblazing, Maps and Maritime Travel. Sara is Director of Studies in History, History and Politics, and History and Modern Languages, Magdalene College. 

Download Sea Control 553 – Tracks on the Ocean with Dr. Sara Caputo

Links

1. Tracks on the Ocean: A History of Trailblazing, Maps and Maritime Travel, by Sara Caputo, Profile Books, September 2024.  

2. Sea Control 353 – The Medical Culture of the British Seaman with Dr. Sara Caputo, by Jared Samuelson, CIMSEC, June 12, 2022.

3. Sea Control 527 – The Wide Wide Sea with Hampton Sides, by Jared Samuelson, CIMSEC, June 13, 2024.

Jared Samuelson is Co-Host and Executive Producer of the Sea Control podcast. Contact him at Seacontrol@cimsec.org.

Podcast

Sea Control 552 – Diego Garcia with Nitya Labh

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By Jonathan Selling

The recent announcement that the United Kingdom will be returning Diego Garcia and the rest of the Chagos Islands to Mauritius brought to an end this long-running dispute. Nitya Labh joins the program to discuss the dispute over the Chagos Islands and the benefit to the UK and US for its return to Mauritius. Nitya Labh is a former James C. Gaither fellow for the South Asia Program and Tata Chair for strategic affairs at the Carnegie Endowment for International Peace. She is an incoming Schwarzman Scholar at Tsinghua University in Beijing.

Download Sea Control 552 – Diego Garcia with Nitya Labh

Links

1. “Why Diego Garcia Matters,” by Nitya Labh, Foreign Policy, May 30, 2024.

Jonathan Selling is co-host and executive producer of the Sea Control podcast. Contact the podcast team at Seacontrol@cimsec.org.

Fostering the Discussion on Securing the Seas.